U.S. patent application number 14/633343 was filed with the patent office on 2016-08-04 for ranking adjustment of federated content items in a social network.
The applicant listed for this patent is LinkedIn Corporation. Invention is credited to Deepak Agarwal, Bee-Chung Chen, Rupesh Gupta, Joshua Daniel Hartman, Cory Michael Hicks, Anand R. Iyer, Keith O. Langston, Jayendraraj Ramamurthi.
Application Number | 20160224559 14/633343 |
Document ID | / |
Family ID | 56553114 |
Filed Date | 2016-08-04 |
United States Patent
Application |
20160224559 |
Kind Code |
A1 |
Hicks; Cory Michael ; et
al. |
August 4, 2016 |
RANKING ADJUSTMENT OF FEDERATED CONTENT ITEMS IN A SOCIAL
NETWORK
Abstract
Systems and methods of ranking adjustment of federated content
items in a social network include causing content items from a
first content item source to be selectively displayed on a user
interface, the content items form the first content item source
being ranked according to a first ranking schema. Content items
from a second content item source are displayed on the user
interface based, at least in part, on a ranking according to a
second ranking schema. Activity data related to interactions with
the content items are obtained from the first content item source.
A utility value adjustment to be applied to the first ranking
schema is determined based on the activity data.
Inventors: |
Hicks; Cory Michael; (San
Jose, CA) ; Iyer; Anand R.; (San Mateo, CA) ;
Langston; Keith O.; (Mountain View, CA) ; Ramamurthi;
Jayendraraj; (San Jose, CA) ; Hartman; Joshua
Daniel; (Mountain View, CA) ; Gupta; Rupesh;
(Sunnyvale, CA) ; Chen; Bee-Chung; (San Jose,
CA) ; Agarwal; Deepak; (Sunnyvale, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
LinkedIn Corporation |
Mountain View |
CA |
US |
|
|
Family ID: |
56553114 |
Appl. No.: |
14/633343 |
Filed: |
February 27, 2015 |
Related U.S. Patent Documents
|
|
|
|
|
|
Application
Number |
Filing Date |
Patent Number |
|
|
62110283 |
Jan 30, 2015 |
|
|
|
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06F 16/24578 20190101;
G06F 16/24575 20190101; G06Q 30/0243 20130101; G06F 16/9535
20190101; H04L 67/26 20130101; G06Q 50/01 20130101; G06F 3/0482
20130101; G06F 16/211 20190101; G06F 16/9577 20190101; G06Q 30/0201
20130101; H04L 67/303 20130101; G06F 16/248 20190101; H04L 67/22
20130101; H04L 67/306 20130101 |
International
Class: |
G06F 17/30 20060101
G06F017/30; G06Q 50/00 20060101 G06Q050/00 |
Claims
1. A system, comprising: a network interface configured to
communicate with a user device via a network; an electronic data
storage including a first content item source and a second content
item source, each of the first and second content item sources
including content items ranked according to a first ranking schema
and a second ranking schema, respectively; and a processor,
configured to: cause, via the network interface, content items from
the first content item source to be selectively displayed on a user
interface; cause, via the network interface, content items from the
second content item source to be displayed on the user interface
based, at least in part, on the second ranking schema; obtain
activity data related to interactions with the content items from
the first content item source; determine a utility value adjustment
to be applied to the first ranking schema based on the activity
data; and cause, via the network interface, content items from the
first and second content item sources to be displayed on the user
interface, content items of the first content item source being
displayed according to the utility value adjustment and the first
ranking schema and the content items of the second content item
source being displayed based, at least in part, on the second
ranking schema.
2. The system of claim 1, wherein the processor is configured to
cause the content items of the first one of the content item
sources to be selectively displayed by randomly varying positions
on the user interface in which the content items are displayed.
3. The system of claim 1, wherein the processor is configured to
cause the content items of the first one of the content item
sources to be selectively displayed by systematically varying
positions on the user interface in which the content items are
displayed.
4. The system of claim 1, wherein the processor is configured to
cause the content items of the first one of the content item
sources to be selectively displayed based on the associated one of
the ranking schemas as unadjusted.
5. The system of claim 1, wherein the processor is configured to
determine the utility value adjustment based on a variation of the
activity data from an expected interaction rate.
6. The system of claim 5, wherein the utility value adjustment is a
percentage difference between a rate at which the activity data
shows interactions with the content items and the expected
interaction rate.
7. The system of claim 1, wherein, for each of the content items of
the first content item source, the processor is further configured
to individually compute a utility value based on the first ranking
schema and the utility value adjustment, wherein, for each of the
content items of the second content item source, the processor is
further configured to individually compute the utility value based,
at least in part, on the second ranking schema, and wherein the
processor is configured to cause the content items to be displayed
according to their respective utility values.
8. The system of claim 7, wherein the processor is further
configured to individually compute the utility value for the
content items of the second content item source further based on a
second utility value adjustment for the second content item
source.
9. The system of claim 8, wherein the processor is further
configured to: cause, via the network interface, content items from
the second content item source to be selectively displayed on a
user interface; obtain activity data related to interactions with
the content items from the second content item source; and
determine the second utility value adjustment based on the activity
data.
10. The system of claim 7, wherein the processor is configured to
cause the content items of the first and second content item
sources to be displayed on the user interface in positions
according to their utility values as individually computed.
11. A method, comprising: causing, with a processor, via a network
interface, content items from a first content item source to be
selectively displayed on a user interface, the first content item
source begin stored in an electronic data storage, the content
items form the first content item source being ranked according to
a first ranking schema; causing, with the processor, via the
network interface, content items from a second content item source,
from the electronic data storage, to be displayed on the user
interface based, at least in part, on a ranking according to a
second ranking schema associated with the second content item
source; obtaining, with the processor, activity data related to
interactions with the content items from the first content item
source; determining, with the processor, a utility value adjustment
to be applied to the first ranking schema based on the activity
data; and causing, with the processor, via the network interface,
content items from the first and second content item sources to be
displayed on the user interface, content items of the first content
item source being displayed according to the utility value
adjustment and the first ranking schema and the content items of
the second content item source being displayed based, at least in
part, on the second ranking schema.
12. The method of claim 11, wherein causing the content items of
the first one of the content item sources to be selectively
displayed is by randomly varying positions on the user interface in
which the content items are displayed.
13. The method of claim 11, wherein causing the content items of
the first one of the content item sources to be selectively
displayed is by systematically varying positions on the user
interface in which the content items are displayed.
14. The method of claim 11, wherein causing the content items of
the first one of the content item sources to be selectively
displayed is based on the associated one of the ranking schemas as
unadjusted.
15. The method of claim 11, wherein determining the utility value
adjustment based on a variation of the activity data from an
expected interaction rate.
16. The method of claim 15, wherein the utility value adjustment is
a percentage difference between a rate at which the activity data
shows interactions with the content items and the expected
interaction rate.
17. The method of claim 11, further comprising: computing
individually, for each of the content items of the first content
item source, a utility value based on the first ranking schema and
the utility value adjustment; and computing individually, for each
of the content items of the second content item source, the utility
value based, at least in part, on the second ranking schema; and
wherein causing the content items to be displayed is according to
their respective utility values.
18. The method of claim 17, wherein computing individually the
utility value for the content items of the second content item
source further based on a second utility value adjustment for the
second content item source.
19. The method of claim 18, further comprising: causing, with the
processor, via the network interface, content items from the second
content item source to be selectively displayed on a user
interface; obtaining, with the processor, activity data related to
interactions with the content items from the second content item
source; and determining, with the processor, the second utility
value adjustment based on the activity data.
20. The method of claim 17, wherein causing the content items of
the first and second content item sources to be displayed on the
user interface is in positions according to their utility values as
individually computed.
Description
PRIORITY
[0001] This application claims the benefit of priority to U.S.
Provisional Application No. 62/110,283, "SOCIAL NETWORK CONTENT
FEDERATION", filed Jan. 30, 2015, which is incorporated by
reference herein in its entirety.
TECHNICAL FIELD
[0002] The subject matter disclosed herein generally relates to the
federation of content from multiple content sources in a social
network.
BACKGROUND
[0003] Social networks conventionally obtain content items from
multiple content item sources. The content items as obtained may
then be displayed to users of the social network on a user
interface, such as a news stream, dedicated windows or spaces on a
visual display, separate windows, and the like. Content item
sources may include user profiles and changes thereto stored by the
social network, entities that provide sponsored content or
databases in which the content items are stored, and organic
content recommendation engines, such as engines that provide
particular types of content, including job recommendations,
recommended connections with members of the social network, and
content that other members and users of the social network have
found interesting.
BRIEF DESCRIPTION OF THE DRAWINGS
[0004] Some embodiments are illustrated by way of example and not
limitation in the figures of the accompanying drawings.
[0005] FIG. 1 is a block diagram illustrating various components or
functional modules of a social network system, consistent with some
examples.
[0006] FIG. 2 is a simplified illustration of a social network
system including content item sources in relation to the federator
module, in an example embodiment.
[0007] FIG. 3 is a detailed block diagram of a federator module, in
an example embodiment.
[0008] FIG. 4 is a simplified image of a user interface as provided
by a social network system, in an example embodiment.
[0009] FIG. 5 is a graphic illustration of a relationship between
the selection metric and the value metric, in an example
embodiment.
[0010] FIG. 6 is a flowchart for ranking adjustment of federated
content items in a social network, in an example embodiment.
[0011] FIG. 7 is a block diagram illustrating components of a
machine, according to some example embodiments.
DETAILED DESCRIPTION
[0012] Example methods and systems are directed to the federation
of content from multiple content sources in a social network.
Examples merely typify possible variations. Unless explicitly
stated otherwise, components and functions are optional and may be
combined or subdivided, and operations may vary in sequence or be
combined or subdivided. In the following description, for purposes
of explanation, numerous specific details are set forth to provide
a thorough understanding of example embodiments. It will be evident
to one skilled in the art, however, that the present subject matter
may be practiced without these specific details.
[0013] In various examples of social networks, the sources of
content items may push content items to be displayed on a user
interface based on criteria, the combination of which are unique to
the content item source or which are not necessarily common to all
of the content item sources. Thus, for instance, a sponsored
content item source may factor in criteria such as an amount that a
sponsoring entity has bid to place a sponsored content item in a
user's news feed while a job recommendation engine may utilize
criteria that focus on a user's qualifications for the job and
their current employment status. Such diverse content item sources
with selection criteria that are specific to the content items
provided by the various individual content item sources may
contribute to a rich and diverse user experience with the social
network.
[0014] However, such arrangements may not be sensitive to the
quality of the content item sources and the need or desire to
balance the display of the content items obtained therefrom
appropriately. In particular, if a content item source has a
relatively poor selection criteria then the content items provided
by the content item source may be of similarly poor quality or
relevance to the user to whom the content items are displayed.
Furthermore, a single content item source may provide more content
items than are necessarily desired without the capacity for the
social network provider to understand if the large numbers of
content items are desirable because they are highly relevant to the
user or undesirable because they are of poor or middling quality
and their sheet number may be overwhelming or may diminish the user
experience.
[0015] A content source federator has been developed that may
address the above issues, among others, by obtaining content items
from the various content item sources according to the individual
content item sources' own selection criteria. The federator may
assess some or all of the content item sources for relative quality
and/or reliability and adjust the perceived value of the content
items received from the respective content item sources
accordingly. The federator may then provide the content items
received from the individual content item sources according to the
adjusted value of the content items and according to any of a
variety of considerations that may reflect on what content items
are presented to the users of the social network.
[0016] FIG. 1 is a block diagram illustrating various components or
functional modules of a social network system 100, consistent with
some examples. A front end 101 consists of a user interface module
(e.g., a web server) 102, which receives requests from various
client-computing devices, and communicates appropriate responses to
the requesting client devices. For example, the user interface
module(s) 102 may receive requests in the form of Hypertext
Transport Protocol (HTTP) requests, or other web-based, application
programming interface (API) requests. An application logic layer
103 includes various application server modules 104, which, in
conjunction with the user interface module(s) 102, may generate
various user interfaces (e.g., web pages, applications, etc.) with
data retrieved from various data sources in a data layer 105. In
some examples, individual application server modules 104 may be
used to implement the functionality associated with various
services and features of the social network service. For instance,
the ability of an organization to establish a presence in the
social graph of the social network system 100, including the
ability to establish a customized web page on behalf of an
organization, and to publish messages or status updates on behalf
of an organization, may be services implemented in independent
application server modules 104. Similarly, a variety of other
applications or services that are made available to members of the
social network service may be embodied in their own application
server modules 104. Alternatively, various applications may be
embodied in a single application server module 104. In some
examples, the social network system 100 includes a content item
publishing module 106, such as may be utilized to receive content,
such as electronic messages, posts, links, images, videos, and the
like, and publish the content to the social network.
[0017] One or more of the application server modules 104, the
content item publishing module 106, or the social network system
100 generally may include a search module 108. As will be disclosed
in detail herein, the search module 108 may identify websites or
content items for display based on a search term as entered by a
searcher. The search module 108 may utilize member profiles and
user activities in the generation of search results. Such member
profiles and activities may be from the searcher making a present
search or by searches performed by the same or other users in the
past. The search module 108 may generate results for a search based
on the member profiles and activities as well as conventional
search factors, such as keywords and link density.
[0018] The search module 108 may be implemented on a separate
server or may be part of a server that provides other portions of
the social network system 100. Thus, it is to be understood that
while the search module 108 is described as an integral component
of a social network, the principles described herein may be applied
without the search module 108 being an integral part of a social
network or even necessarily utilizing data from a social network if
content items 122 are available from alternative sources.
[0019] As illustrated, the data layer 105 includes, but is not
necessarily limited to, several databases 110, 112, 114, such as a
database 110 for storing profile data 116, including both member
profile data as well as profile data for various organizations.
Consistent with some examples, when a person initially registers to
become a member of the social network service, the person may be
prompted to provide some personal information, such as his or her
name, age (e.g., birthdate), gender, interests, contact
information, home town, address, the names of the member's spouse
and/or family members, educational background (e.g., schools,
majors, matriculation and/or graduation dates, etc.), employment
history, skills, professional organizations, and so on. This
information is stored, for example, in the database 110. Similarly,
when a representative of an organization initially registers the
organization with the social network service, the representative
may be prompted to provide certain information about the
organization. This information may be stored, for example, in the
database 110, or another database (not shown). With some examples,
the profile data may be processed (e.g., in the background or
offline) to generate various derived profile data. For example, if
a member has provided information about various job titles the
member has held with the same or different companies, and for how
long, this information can be used to infer or derive a member
profile attribute indicating the member's overall seniority level,
or seniority level within a particular company. With some examples,
importing or otherwise accessing data from one or more externally
hosted data sources may enhance profile data for both members and
organizations. For instance, with companies in particular,
financial data may be imported from one or more external data
sources, and made part of a company's profile.
[0020] Once registered, a member may invite other members, or be
invited by other members, to connect via the social network
service. A "connection" may require a bi-lateral agreement by the
members, such that both members acknowledge the establishment of
the connection. Similarly, with some examples, a member may elect
to "follow" another member. In contrast to establishing a
connection, the concept of "following" another member typically is
a unilateral operation, and at least with some examples, does not
require acknowledgement or approval by the member that is being
followed. When one member follows another, the member who is
following may receive status updates or other messages published by
the member being followed, or relating to various activities
undertaken by the member being followed. Similarly, when a member
follows an organization, the member becomes eligible to receive
messages or status updates published on behalf of the organization.
For instance, messages or status updates published on behalf of an
organization that a member is following will appear in the member's
personalized data feed or content stream. In any case, the various
associations and relationships that the members establish with
other members, or with other entities and objects, are stored and
maintained within the social graph database 112.
[0021] Activities by users of the social network system 100,
including past searches that have been conducted by the search
module 108, may be logged as activities 118 in the activity and
behavior database 114. Such activities may include search terms,
interactions with search results and subsequent engagement with the
subject of search results, scores assigned to such search terms, as
disclosed herein, communication with others via the social network,
engagement with content items posted on the social network, joining
groups, following entities, and so forth.
[0022] The data layer 105 collectively may be considered a content
item database, in that content items 120, including but not limited
to member profiles 116, may be stored therein. Additionally or
alternatively, a content item layer 120 may exist in addition to
the data layer 105 or may include the data layer 105. The content
item layer 120 may include individual content items 122 stored on
individual content item sources 124. The member profiles 116 and
the activities 118 may be understood to be content items 122, while
the profile database 110, the social graph database 112, and the
member activity database 114 may also be understood to be content
item sources 124. Content items 122 may further include sponsored
content items as well as posts to a newsfeed, articles or links to
websites, images, sounds, event notifications and reminders,
recommendations to users of the social network for jobs or entities
to follow within the social network, and so forth.
[0023] The social network service may provide a broad range of
other applications and services that allow members the opportunity
to share and receive information, often customized to the interests
of the member. For example, with some examples, the social network
service may include a photo sharing application that allows members
to upload and share photos with other members. With some examples,
members may be able to self-organize into groups, or interest
groups, organized around a subject matter or topic of interest.
With some examples, the social network service may host various job
listings providing details of job openings with various
organizations.
[0024] Although not shown, with some examples, the social network
system 100 provides an application programming interface (API)
module via which third-party applications can access various
services and data provided by the social network service. For
example, using an API, a third-party application may provide a user
interface and logic that enables an authorized representative of an
organization to publish messages from a third-party application to
various content streams maintained by the social network service.
Such third-party applications may be browser-based applications, or
may be operating system-specific. In particular, some third-party
applications may reside and execute on one or more mobile devices
(e.g., phone, or tablet computing devices) having a mobile
operating system.
[0025] FIG. 2 is a simplified illustration of the social network
system 100 including the content item sources 124 in relation to
the federator module 108, in an example embodiment. The social
network system 100 may allow for the content item sources 124 to be
combined into a single feed for transmission to and/or display on a
user interface of a member or user of the social network. In an
example, some or all of the content item sources 124 are
implemented as an API, such as an http API.
[0026] The content item sources 124 may rank the content items 122
stored therein according to the ranking parameters of the content
item source 124. Such content item sources 124 may include content
item sources disclosed in U.S. Patent Application Publication No.
2014/0143163, "USER CHARACTERISTICS-BASED SPONSORED JOB POSTINGS",
U.S. Patent Application Publication No. 2014/0143323, "USER
CHARACTERISTICS-BASED SPONSORED COMPANY POSTINGS", and U.S. Patent
Application Publication No. 2015/0039406, "INDEPENDENT TARGETED
SPONSORED CONTENT MANAGEMENT SYSTEM AND METHOD", all of which are
incorporated by reference herein in their entirety. The content
item sources 124 may thus function as first past rankers of the
content items 122 stored therein or obtained thereby.
[0027] The federator module 108 may then rank the content items 122
provided to the federator module 108 by the content item source
124. As such, the federator module 108 may function as a second
pass ranker. Based on the content items 122 as ranked by the
federator module 108, the federator module 108 may produce as
output a content item 122 stream 200 that may be an http API or any
of a variety of other suitable formats known in the art. The
content item stream 200 may be utilized by the messaging publishing
module 106 and/or the user interface module 102 to provide the
output to the user interface of the user or member.
[0028] A protocol may be defined between the federator module 108
and the content item sources 124. The federator module 108 may
utilize the protocol to make requests to the content item sources
124 for ranked content items 122 from some or all of the sources
124. The requests may be according to a conventional http protocol.
The content item sources 124 may similarly respond according to a
conventional http data transfer.
[0029] The content item sources 124 may include or may be modified
to include one or more files or programs that allow the ranked
content items 122 to be transmitted and formatted according to the
protocol. In an example, an object notation standard may be
utilized to generate the data transfer of ranked content items 122.
In an example, the JavaScript Object Notation (JSON) standard may
be utilized. Libraries that may programmatically generate libraries
that may read, validate, serialize, and deserialize the data
transfer into language specific data structures. In the above
example utilizing the JSON standard, the data structures may be
Java objects.
[0030] As such, the one or more files or programs may include a
product specification file that may be incorporated into a trunk
directory of one or more of the content item sources 124.
Additionally, a project build file may likewise be incorporated. A
common key, in the above example a JSON coordinate, may be utilized
between the product specification file and the project build
file.
[0031] A user interface metrics module 202 may identify content
items 122 that produce or do not produce a user interaction with
the content item 122 when displayed on a user interface 204 of a
user device. In various examples, if a user interacts with a
content item 122 as displayed on the user interface 204, such as by
clicking a link, sharing the content item 122, commenting on the
content item 122, and so forth, the user interface metrics module
202 variously either receives the interaction directly or receives
an indication of the interaction. For instance, receiving the
interaction itself may be to receive the text of a comment that was
entered while receiving an indication of the interaction may be to
receive a notice that a comment was entered without receiving the
comment itself. The user interface metrics module 202 is optionally
coupled to the content item sources 124 and may save the
interactions as received, such as in the activities database
114.
[0032] The social network system 100 may provide content items 122
to the user interface 204 in a federating mode and a testing mode.
The social network system 100 may switch between modes from time to
time and from user to user. Thus, some users may receive content
items 122 as provided by the federator module 108 and other users
may receive content items 122 with the operation of the federator
module 108 reduced or disabled altogether. In the testing mode, as
will be discussed in detail herein, the impact of the operations of
the content item sources 124 and their function as first-pass
rankers may be assessed using the user interface metrics module 202
by varying the display of content items 122 on the user interface
204. In the federating mode the federator module 108 may utilize
the assessments provided by the user interface metrics module 202
to determine the relative effectivity of the content item sources
124 at assessing the content items 122 stored thereon and adjust
the resultant display of content items 122 on the user interface
204.
[0033] The testing mode may be selectively applied to particular
components of the social network system 100 to obtain particular
information, as disclosed herein. In various examples, individual
content item sources 124 may be selectively placed in testing mode
and their output randomly or varyingly presented to the user while
the output of other content item sources 124 may be presented to
users according to federation policies implemented by the federator
module 108. In such examples, newly added or modified content item
sources 124 may be dynamically tested and their results compensated
for, as disclosed herein, while other content item sources 124,
such as those that have already been assessed in the testing mode
and incorporated into the federation protocol as disclosed herein
may operate statically outside of the testing mode.
[0034] FIG. 3 is a detailed block diagram of the federator module
108, in an example embodiment. In such an example, the federator
module 108 is a separately implemented http server. The federator
module 108 includes a ranker module 300, a feed definition module
302, recommender modules 304, and entity resolver modules 306. The
some or all of the various modules 300, 302, 304, 306 may be
separately implemented files operated on a processor of the server
or may be divided between and among multiple servers.
[0035] The ranker module 300 may obtain collections of content
items 122 retried from the content item sources 124 as specified by
the feed definition module 302. The ranker module 300 may
de-duplicate the content items 122 from the various sources 124,
may perform a second-pass or global ranking of the content items
122, and may provide the result as the output of the federator
module 108.
[0036] The feed definition module 302 may provide the content items
122 or cause the content items 122 to be provided to the ranker
module 300. The feed definition module 302 may map an identifier of
the feed to be output on to the recommender modules 304 and the
ranker module 300. Thus, content items 122 may be identified in the
recommender modules 304 and provided to the ranker module 300 based
on the identifier.
[0037] The recommender modules 304 may define a mapping between the
content item sources 124 and a recommender that will provide
content items 122 based on a request for content items 122 to be
provided and one or more of the resolver modules 306. The resolver
modules 306 may optionally covert a format of content items 122 as
obtained from the content item sources 124 to a common format.
[0038] FIG. 4 is a simplified image of a user interface 204 as
provided by the social network system 100, in an example
embodiment. The user interface 204 includes a news feed 400 that
includes multiple individual positions 402 arranged, in this
example, in a vertical list with a first position 402(1) at the top
and lower positions sequentially down the list. Each position 402
includes space to display content related to the content item 122;
in various examples, the content item 122 itself may be displayed,
for instance if the content item 122 is a link or a renderable
image, or data relating to the content item 122 may be displayed,
such as if the content item 122 needs to be reformatted for the
user interface 204 or the circumstances in which the user interface
204 is being displayed. It is to be recognized that the user
interface 204 is provided for the purposes of an example and that
many additional configurations of user interfaces 204 are
contemplated and may be utilized consistent with the principles
described herein.
[0039] The social network system 100 may operate in the testing
mode described above by obtaining content items 122 from the
content item sources 124 and displaying the content items 122 on
the user interface 204 without respect to the federator module 108.
As such, the content item sources 124 may function in their
first-pass ranker mode without second-pass ranking provided by the
federator module 108. In various examples, the content items 122
may still pass through the federator module 108, as illustrated in
FIG. 2, but the second-pass ranking function of the federator
module 108 may be disabled.
[0040] In an example, at least one of the federator module 108 and
the message publishing module 106 call to a content item source 124
to obtain at least one content item 122 for display on the user
interface 204. The content item 122 may then be displayed in a
particular position 402 of the news feed 400. In an example, the
position 402 is randomly selected or pseudo-randomly selected. In
an example, the content item 122 may be displayed on multiple user
interfaces 204 corresponding to multiple different users. In such
an example, a given content item 122 may be iteratively moved from
position 402 to position 402 when it is displayed on multiple user
interfaces 204 so as to sequentially be positioned in a variety of
positions 402 over time. Additional content items 122 may be
obtained from various content item sources 124 and positioned
randomly or varyingly in positions 402 in the various user
interfaces 204 so as to fill out the positions 402 of the news feed
400.
[0041] In addition to the content items 122 themselves, the content
item sources 124 may provide the first-pass ranking details of each
content item 122 to the user interface metrics module 202. It is
noted and emphasized that, in the testing mode, the content items
122 as provided may not necessarily be placed according to the
first-pass ranking provided by the content item sources 124.
However, the data from the first-pass ranking may be utilized by
the user interface metrics module 202 to assess the quality of the
first-pass ranking of the various content item sources 124.
[0042] As displayed on the various user interfaces 124, the content
items 122 may be interacted with, as disclosed herein. The user
interface metrics module 202 may note those interactions for each
content item 122 and/or the lack of interactions thereof. In
various examples, the user interface metrics module 202 may also
optionally note the position 402 in which the content item 122 was
displayed when it was or was not interacted with. It is noted that
the position 402 may be superfluous if the content item 122 is
displayed randomly or sequentially varying on a relatively large
number of user interfaces 204.
[0043] For a given content item 122 as displayed on user interfaces
204, the user interface metrics module 202 may note the rate at
which the content item 122 was the subject of a user interaction in
comparison with the first-pass ranking that the content item source
124 provided for the content item 122. The user interface metrics
module 202 may compare those figures with the expected interaction
performance of a content item 122 that has been placed in the
positions in which the given content item 122 has been placed.
[0044] The various content item sources 124 may perform first-pass
ranking and other assessments according to schemas that are not
consistent among all of the content item sources 124. Thus, in an
example, a first content item sources 124 may operate according to
a first selection schema that seeks to determine a selection metric
indicative of the likelihood that a given content item 122 will be
interacted with by a user. The first content item source 124 may
further operate according to a first value schema that seeks to
determine a value metric of a content item 122 as if the content
item 122 were a piece of sponsored content. It is noted that, if
the content item 122 is, in fact, a piece of sponsored content, and
the content item source 124 is, for instance, an advertising index,
the actual bid for the sponsored content item may be the value
metric. The value metric may, in various examples, be a value in a
currency, such as United States dollars or other national or
international currency.
[0045] In contrast to the first content item source 124, the second
content item source 124 may operate according to a second selection
schema different from the first selection schema and a second value
schema different from the first value schema. Most generally,
selection schemas and value schemas may differ between content item
sources 124 if the same content item 122 receives a different
selection metric when run against the first selection schema and
the second selection schema. It is to be noted, however, that most
or all content items 122 may only be run against one selection
schema and one value schema because content items 122 may tend only
to be stored in one content item source 124.
[0046] For instance, in the illustrative example, for a sample
content item 122, the content item source 124 may provide a
first-pass rank that suggests that the content item 122 is at the
seventy-fifth (75.sup.th) percentile for likely user interaction
and should optimally be placed in the third position 402(3). In the
example, the user interface metrics module 202 has previously
determined that, on average, a content item 122 randomly placed in
the news feed 400 that is expected to be in the seventy-fifth
percentile and/or is placed in the third position 402(3) is
interacted with by a user, on average, eleven (11) percent of the
time. In the illustrative example, the user interface metrics
module 202 determines that, overall, the sample content item 122 is
interacted with thirteen (13) percent of the time both overall and
in the third position 402(3).
[0047] On that basis, the user interface metrics module 202 may
determine that the content item source 124 that provided the
content item 122 understates or underestimates the likely
performance of the content items 122 it ranks. The user interface
metrics module 202 may perform the testing mode analysis on
multiple content items 122 from multiple content item sources 124.
Ultimately, the user interface metrics module 202 may characterize
some or all of the content item sources 124 according to the degree
by which the content item sources 124 overestimate or underestimate
the likely user interaction with the content items 122 the content
item source 124 provides. Thus, for the content item source 124
that provided the sample content item 122 referenced above, the
user interface metrics module 202 may utilize dozens or more
content items 122 from the content item source 124 to determine
that the content item source 124 consistently underestimates the
user engagement rate for the content items 122 it provides by two
(2) percentage points. Other content item sources 124 may be
determined to overestimate by various percentages or be essentially
accurate in their assessments.
[0048] In the federating mode, the federator module 108 may obtain,
from the various content item sources 124, content items 122 and an
associated selection metric and an associated value metric for each
content item 122. The federator module 108 may request a
predetermined number of content items 122 from some or all of the
content item sources 124 or the content item sources 124 may
individually determine how many content items 122 to send to the
federator module 108. It is to be further recognized that the
content item sources 122 may, at least initially, transmit a list
or index of content items to the federator module 108 at least
until the content items 122 are selected by the federator module
108 for display on the user interface 204, upon which point the
content items 122 themselves may be provided.
[0049] The federator module 108 may further obtain, from the user
interface metrics module 202, indications of the interactions with
the content items 122 from the various content item sources 124.
The indications of the interactions may be on the basis of
individual content items 122 that have been tested in the testing
mode or on the basis of complete content item sources 124 that have
been tested in the testing mode.
[0050] The federator module 108 may determine an engagement value
for each of the content items based on the data from the user
interface metrics module 202. The engagement value may be
representative of the inherent value of the content itself to the
social network without respect to any money the content item 122
may actually earn for the social network system 100. Put another
way, the engagement value may reflect the overall value to the
social network of having good content to drive traffic to the
social network without respect to directly making money off of that
content.
[0051] In an example, the inherent value represented by the
engagement value may vary, at least in part, based on either the
user from whom the content item 122 was received or to whom the
content item is to be displayed. Thus, certain content items 122
may have a higher engagement for certain types of users than other
types of users. The federator module 108 may adjust the engagement
value for a content item 122 based on user profile data 116 and
activities 118 for the user to whom the content item is displayed.
Thus, for instance, the engagement value for a content item 122
received from a CEO may be doubled relative to the engagement value
for a content item 122 received from a non-managerial employee of
the same company.
[0052] If the user interface metrics module 202 provided data for
the particular content item 122 then the engagement value may be
based only on the data related to that content item 122. If the
user interface metrics module 202 provided data for the content
item source 124 then all of the content items 122 from that source
124 may have an engagement value determined based on the same
factors.
[0053] The engagement value may be the equivalent to a monetary
value that, in essence, adjusts the selection metric and value
metric of the content item 122 to account for the overestimation or
underestimation of the likely interaction or value of the content
item 122 by the selection and value schemas of the content item
source 124. Thus, for instance, in the above example, the federator
module 108 may determine that the value of a content item 122 from
the sample first content item source 124 described above should be
increased by $0.005 to account for the fact that the content items
122 from that source routinely underestimates the user interaction
with the content items 122 by two (2) percentage points.
[0054] It is to be emphasized that the engagement and monetary
values are, in fact, unit-less and may have any suitable numerical
value. For the purposes of explanation in the disclosure herein,
the values disclosed herein have been normalized to an equivalent
monetary value. Thus, in a simplified description for the purposes
of illustration, the engagement value is in essence described as
being calculated as an equivalent monetary value and combined with
an actual monetary value to create the utility value of equivalent
monetary value. However, it is to be noted and emphasized that the
utility value does not need to represent an equivalent monetary
value and rather can be directed at any "value" that administrators
of the social network may have.
[0055] Thus, while the steps described herein may relate to
bringing the engagement value into line with the monetary value,
the opposite may readily be implemented to bring the monetary value
in alignment with the engagement value according to the same
principles. Thus, in a simplified example, one user interaction
with a content item may have an engagement value of "1", and
monetary values may, for instance, be multiplied by a factor of
twenty (20); i.e., a monetary value of $0.005 is the equivalent to
one interaction. It is to be readily understood that any suitable
values value ranges may be implemented.
[0056] As such, the utility value may express a propensity for an
associated content item to lead to any outcome that has value to
the social network. In an example, the utility value may be tied to
a number of "down-stream" interactions that may stem from an
initial interaction with a content item. A down-stream interaction
may stem from, for instance, a member selecting a link for a
content item as the initial interaction, and any subsequent
selections of links or comments and the like on the webpage that
was linked to would be a down-stream interaction. The relative
value of down-stream interactions may be identified based on social
network policies in relation to the value of sponsored content
items and implemented according to the principles described herein.
Further examples of the actual policy or objective of the utility
value, such as growth of the membership of the social network, may
similarly be implemented according to these principles. As such,
federator module 108 may be sensitive to the impact on those
objectives that the changes to the initial rankings of the content
item sources may cause and adjust the changes accordingly.
[0057] FIG. 5 is a graphic illustration 500 of the relationship
between the selection metric and the value metric, in an example
embodiment. The x-axis 502 depicts the selection metric, such as
the number of user interactions with a content item, while the
y-axis 504 depicts the value metric, such as the value of the
content item 122 if it were a piece of sponsored content. The curve
506 reflects how changes in the selection metric are reflected in
the changes in the value metric and, as a consequence, the
engagement value of the content item 122. According to this curve,
increasing the selection metric by two (2) percentage points from a
first point 508 to a second point 510 may produce the $0.005
engagement value referenced above.
[0058] The federator module 108 may then generate a utility value
for each of the content items 122. The utility value reflects an
engagement component and a monetary component. The engagement
component is, in an example, comprised of the selection metric
multiplied by the engagement value. The value component is, in an
example, comprised of the value metric. The engagement component
and the value component are, in an example, added together to
obtain the utility value. The utility value may represent a
normalized value for the content item 122. In various examples, the
federator module obtains a utility value for each of the content
items obtained from the content item sources 124.
[0059] In an example, the utility value will depend on a status of
the content item 122 as organic content or sponsored content. The
utility value of a sponsored content item may be the engagement
component (e.g., the engagement value multiplied by the selection
metric) added to the value metric. The value metric for the
sponsored content item may be a bid that the sponsoring entity has
paid or will pay for the sponsored content item multiplied by the
selection metric. In an example, the value metric is thus computed
by multiplying the estimated interaction rate for the sponsored
content item by the amount of money the sponsoring entity promised
to pay every time the sponsored content item is selected by a user.
Thus, the utility value for a sponsored content item would be the
sum of the expected monetary value of the sponsored content item
and the engagement value of the sponsored content item. Put another
way, the value of a sponsored content item may be realized in both
the ability of the content item 122 to drive user engagement with
the social network and the ability of the content item 122 to
directly generate revenue.
[0060] The utility value of an organic or unsponsored content item,
on the other hand, would, in the above example, be based entirely
on the ability of the content item 122 to generate engagement with
the social network. Thus, the utility value for the organic content
item would be only the engagement component (the engagement value
multiplied by the selection metric). Thus, it may be discerned that
a piece of organic content that drives a great deal of user
engagement may have a higher utility value than a piece of
sponsored content that that drives relatively little user
engagement. Further, a piece of sponsored content that has the same
or similar user engagement as an organic content item would have
the higher utility value because of the monetary component; all
other things being equal, the utility value for a content item 122
that is sponsored would be higher than the utility value of a
sponsored content item 122 that is organic.
[0061] The federator module 108 may thus, in essence, establish a
normalized, monetary value for each of the content items 122 it
receives for display on the news feed 400 of the user interface
204. In so doing, the federator module 108 may both consistently
establish the relative value of the content items 122 it receives,
regardless of the first-pass ranker schemas utilized by the content
item sources 124, and provide a framework by which the value of a
sponsored content item may be compared against an organic content
item and vice versa. Thus, both the value of the organic content
items may be quantified and organic content items may be accurately
positioned relative to sponsored content items on the news feed
400.
[0062] In particular, the federator module 108 may include, as part
of the stream 200, the relative utility values of the content items
122 to the user interface module 102. Alternatively, the federator
module 108 may simply order the content items 122 within the stream
200 according to their respective utility values. The user
interface module 102 may then cause the content items 122 to be
sequentially placed in the positions 402, at least in part
according to their utility values. Thus, in an example, the highest
utility value may be positioned in the first position 402(1), the
second highest utility value in the second position 402(2), and so
forth. Alternatively, additional factors may be implemented in
order to meet certain conditions.
[0063] The conditions may, in various cases, specify displaying
sufficient sponsored content items to generate a maximal amount of
revenue while maintaining user engagement, in the form of
interactions with the content items above a predetermined
threshold. Thus, the sum of the engagement components of some or
all of the content items 122 that may be displayed over a period of
time may be plotted against the sum of the value components of the
content items 122 that may be displayed over a period of time. In
selecting the content items 122 for the stream, the federator
module 108 may select content items with sufficiently high
engagement components to maintain the desired user engagement and
then, among that population, select the content items 122 with the
highest value component.
[0064] The above example is simplified and it is to be understood
that multi-objective optimization techniques may be applied to the
population of content items 122 as appropriate. The constraints of
the multi-objective optimization may be applied separately to
different types of users depending on the activities 118 conducted
by the individual users. Thus, certain users may be relatively more
likely to select sponsored content items than other users. Those
users may be presented with more sponsored content items than other
users, thereby potentially increasing both the value metric, as
sponsored content may be directed to the users most likely to
select the sponsored content and thus provide the revenue, as well
as engagement, as more scope may thus be had to display content
items 122 with relatively high engagement components.
[0065] The principles applied to direct knowledge of the propensity
of users to select sponsored content may be applied based on
general user characteristics. Thus, it may be determined that males
of a certain age, education, and career may be relatively more
likely to select sponsored content than women of the same age,
education, and career. Those relationships may be determined
empirically, such as by being objectively determined in the testing
mode. The difference in the likelihood of a certain demographic of
user to select or not select sponsored content may produce a
proportional increase in the rate at which sponsored content is
displayed. Thus, if a certain demographic of user is twenty-five
percent more likely to select a sponsored content item than the
average user then users of that demographic may be presented with
twenty-five percent more sponsored content. Alternatively, the
additional sponsored content a user is presented with may be
selected as a multi-objective optimization variable, such as to
maximize revenue while maintaining user engagement, and may not
necessarily be tied to any particular percentage.
[0066] The federator module 108 may be configured to retain
sponsored content items in a particular order prior to or while
including the sponsored content items in the stream 200. In various
examples, sponsored content items 200 may be ranked with respect to
one another prior to determining and applying the engagement value
to the sponsored content items. After obtaining the engagement
value, the sponsored content items may be re-ranked with respect to
the organic content items. However, in certain examples, the
sponsored content items may not be re-ranked with respect to one
another. Doing so may maintain the relative position of the
sponsored content items for regulatory purposes. The fixing of the
position of certain content items 122 with respect to one another
may be configurable based on any regulatory requirements in any
relevant jurisdictions. The fixing of the position of certain
content items 122 may also be based on business needs or any other
suitable factors.
[0067] The principles described herein with regard to the
federation of individual content items 122 apply as well to the
federation of aggregated content items. An aggregated content item
may be a combination of individual content items 122 combined or
otherwise placed together so that they may be displayed in a signal
position 402, in contrast with conventional, individual content
items 122 which are displayed one per position 402. The aggregated
content item may be made up of individual content items 122 that
are related to one another in some way, such as by being related to
common news or members of the social network who share a common
personal characteristic 116, such as a job, a job status, a school,
and so forth.
[0068] Individual content items 122 as displayed on the news feed
400 may not generate much user interaction by themselves but may
generate more interest when presented as a aggregated content item.
For instance, the news that a first member has changed jobs to
Company X may not generate much interest by itself. However, an
aggregated content item that seven members have all changed jobs to
Company X in the last three days may generate much more user
interaction than seven separately-listed content items 122.
[0069] An aggregated content item 122A is illustrated in the user
interface 204 in FIG. 4. In contrast to conventional content items
122, the aggregated content item references more than one discrete
event, occurrence, or member. Thus, the aggregated content item
122A states that members X, Y, and Z all joined Company A in the
last two days. A conventional, non-aggregated content item 122
might merely state that member X joined Company A yesterday, by way
of illustration.
[0070] The federator module 108 may be configured to rank the
aggregated content item 122A consistent with the ranking of other
content items 122 described herein. That is to say, the federator
module 108 may determine a utility value for the aggregated content
item 122A based on an engagement value of the aggregated content
item 122A and, if the aggregated content item 122A is a sponsored
aggregated content item 122A or includes at least some sponsored
content, a monetary value as well.
[0071] In an example, a distribution of utility values of the
constituent content items 122 of the aggregated content item 122A
may be utilized to determine the utility value of the aggregated
content item 122A. The distribution of utility values of the
constituent content items 122 may also be utilized by the federator
module 108 to determine if individual content items 122 should be
removed from the aggregated content item 122A in order to improve
the overall utility value of the content items 122 included in the
aggregated content item 122A. While utility values will be
discussed herein, it is to be recognized and understood that any of
a variety of metrics may be utilized for decision regarding the
aggregation of content items. For instance, basic estimated
selection metrics, such as estimated interactions or
click-through-rates, may be utilized in addition to or instead of
the utility value.
[0072] To determine the utility value of an aggregated content item
122A or, in various examples, a proposed aggregated content item
122A, the federator module 108 utilize multiple models based on
various factors. The models may be empirically determined based on
arbitrarily generating aggregated content items 122A in the testing
mode described herein and randomly presenting those aggregated
content items 122A on user interfaces 204. In various examples,
individual models are based on a distribution of utility values of
the constituent content items 122, a time since or over which the
content items 122 were obtained or generated, and an overall number
of content items 122 in the news feed 400.
[0073] The distribution model may be based on an average of utility
values of individual content items 122, a maximum one of the
utility values of the individual content items 122, a minimum one
of the utility values of the individual content items 122, and a
standard deviation of the utility values of the individual content
items 122, among other potential factors. The interplay of those
factors may be determined empirically. In an example, the
distribution model may determine the utility value of the
aggregated content item 122 by computing the average utility value
of the constituent content items 122 and adjusting for the standard
deviation of the utility values of the content items 122.
[0074] Thus, for instance, it may have been empirically determined
that the distribution model tends to produce an accurate utility
value for the aggregated content item 122A based on the average of
the utility values of the individual content items 122A adjusted
upward for a relatively small standard deviation and adjusted
downward for a relatively large standard deviation. For instance, a
standard deviation less than twenty-five percent of the average may
be "small" and provide a bonus while a standard deviation greater
than or equal to twenty-five percent may be "large" and provide a
penalty. The bonuses and penalties may be proportional to size of
the standard deviation. By way of illustration, if the average
utility value is 0.005 and the standard deviation is 0.001 then the
utility value of the aggregated content item may be
0.005+10*(0.00125-0.001)=0.0075, where the "0.005" value is the
average utility value of the content items 122, the "0.00125" value
is twenty-five percent of the average, the "0.001" value is the
standard deviation, and the "10" value is an empirically-determined
bonus multiplier. The distribution model, then, would provide a
utility value for the aggregated content item 122A of 0.0075.
[0075] The time and amount of content items 122 models may function
in the same or similar ways. The time model may assign bonus
utility values to content items 122 based on a time since the
content item 122 in question was generated. The utility values may
be assigned based on an empirically-determined decay model. For
example, a content item 122 that is less than one day old may have
a bonus utility value of 0.001, more than one but less than two
days old may be 0.0005, more than two but less than three days may
be 0.0025, and so forth. The utility values for the time model may
then be combined utilizing some or all of the factors for the
distribution model, e.g., average, minimum, maximum, and standard
deviation.
[0076] Relatedly, the overall number of content items 122 in the
news feed 400 may tend to factor the utility values of individual
content items 122 over the utility value of the aggregated content
item 122A so as to provide more or fewer content items 122 for the
news feed 400. Thus, if the federator module 108 has relatively few
content items 122 for the news feed 400 then the individual content
items 122 of the aggregated content item 122A may be given a
relatively high bonus utility value while the aggregated content
item 122A as a whole may be given a relatively low bonus utility
value. By so doing, the content items 122 of the aggregated content
item 122A may be more likely to be broken out of the aggregated
content item 122A and presented individually on the news feed 400.
Conversely, if the federator module 108 has a relatively large
number of available content items 122 then the federator module 108
may subtract utility value from the content items 122 of the
aggregated content item 122A, making the content items 122 more
likely to remain part of the aggregated content item 122A.
[0077] The individual models may all be individually implemented
and then manipulated together or otherwise compared. In an example,
the individual models may be averaged or may be added together to
obtain a final utility value for the aggregated content item 122A.
Alternatively, only one determined utility value may be utilized,
for instance by selecting a maximum value, minimum value, or middle
value among the utility values provided by the various models.
Further alternatively, individual models may be separately assessed
in the testing mode and given bonus or negative weight or otherwise
favored or disfavored based on the performance in the testing mode.
Thus, a model that consistently accurately provides a utility value
may be weighted higher than a model that inconsistently provides
accurate utility values. Alternatively, only the best single model
may be utilized, though other models may be used, particularly in
testing mode, to seek to improve the results of the models and
utilize the models at a later date.
[0078] Based on the final utility value for the aggregated content
item 122A, the federator module 108 may display the aggregated
content item 122A in an appropriate position 402 depending on the
utility values of other content items 122, not display the
aggregated content item 122A at all, and/or separate individual
content items 122 out of the aggregated content item 122A if those
individual content items 122 have utility values greater than the
utility value of the aggregated content item 122A. In an example,
if the aggregated content item has a utility value of 0.003 but one
content item 122 of the aggregated content item 122A has a utility
value of 0.004 and another has a utility value of 0.005 then those
content items 122 may be removed from the aggregated content item
122A. In various examples, the aggregated content item 122A may be
recomputed to determine its new utility value or may be inserted
into the stream 200 in a position appropriate to its utility
value.
[0079] The utility values of content items 122 (including herein
both individual content items 122 and aggregated content items
122A) may be based on a relevance of the content item 122 to the
profile data 116 and activities 118 of the member to whom the
content items 122 are to be or may be presented. In various
examples, profile data 116 and activities 118 may be utilized by
the federator module 108 along with other factors to adjust the
utility value of content items 122. The federator module 108 may
thus provide content items 122 according to their value to the
member to whom the content items 122 are presented rather than to a
generic or generalized member.
[0080] While the principles related to affinity are described with
respect to utility values, it is to be recognized and understood
that they may apply equally well to circumstances that provide
content items 122 outside of the utility value framework. Thus,
bonuses to simple relevance factors or other metrics by which
content items 122 may be selected for display to users of a social
network may also be applied consistent with this disclosure.
[0081] In an example, the member may have an identifiable item-type
affinity. The member may prefer certain types of content items 122
over others. Similarly, the member may dislike certain types of
content items 122. The affinity for content item 122 types may be
based both on inferences from the profile data 116 of the member
and past history as evidenced by the member's activities 118.
[0082] In an example, a member who has profile data indicating that
they are a computer programmer may tend to have an affinity for
articles and links related to computer programming, computers
generally, engineering generally, and so forth. In an example, the
utility value of such types of content items 122 may be given a
bonus for each profile data item 116 that correlates with the
content item 122 type. Similarly, computer programmers may tend to
be neutral towards other types of content items 122 and may
affirmatively dislike other types of content items 122.
[0083] The federator module 108 may identify such correlations
across multiple members. Thus, the federator module 108 may
identify that computer programmers generally are fifty percent more
likely to interact with content items related to computer
programming than the population of members of the social network
generally. In such an example, the utility value of computer
programming content items 122 may be given a fifty percent bonus.
Alternatively, the bonus may be of a different percentage or may be
a fixed value for matching a type with which the member has an
affinity, e.g., a bonus of 0.001 to the utility value. Any of a
variety of suitable bonuses may be applied, and such bonuses may
also be negative for members who tend to dislike a content item 122
type.
[0084] The principles for profile data 116 apply as well to
activities 118 for a particular member. Thus, if a member's
activities 118 indicate that the member tends to interact with
computer science content items 122 forty percent more frequently
than members of the social network in general, the utility value of
computer science content items 122 may receive a bonus. The bonus
may be according to any suitable mechanism, including the
mechanisms described above.
[0085] The bonuses may be cumulative across multiple profile data
116 and activities 118 for a single content item 122 or may be
based on a single most significant factor. The single most
significant factor may be a member's own activities 118, with
profile data 116 being utilized if in the event the activities 118
are unavailable or not extensive enough to establish a preference.
Thus, if a member's profile data 116 indicates that the member
would be expected to have an affinity for a content item 122 type
but the member's activities 118 indicate that the member dislikes
the content item 122 type then the utility value of the content
item 122 may be reduced rather than increased.
[0086] The principles described with the item-type affinity may be
applied to other concepts as well. In an example, members may have
an affinity for the source of a content item 122 rather than the
content of the content item 122 itself. Thus, members may tend to
click on links in a content item 122 or otherwise interact with a
content item 122 if the content item 122 is provided by a
particular source. Such sources may include individuals, companies,
groups, and the like. Such sources may include the social network
system 100 itself, such as for automatically-generated content
items 122.
[0087] Source affinity may be unique to each member. Thus, source
affinity may be based on activities 118 for the particular member
and may not necessarily be based on profile data 116 of the member.
Alternatively, certain profile data 116 may be indicative of a
propensity for source affinity. Thus, computer programmers may have
a source affinity for certain celebrities in computer programming
that may be factored in in the same manner described above with
respect to profile data 116 and item-type affinity.
[0088] Network-size affinity may also be utilized to provide a
utility value bonus. The social graph data 112 for a member who
posts a content item 122 to the social network may be compared
against the social graph data 112 of a member to whom the content
item 122 may be presented. If the number of connections in the
social graph data 112 of the two members is broadly similar then
the content item 122 may receive a bonus to the utility value for
display on the news feed 400 of the potential receiving member. In
an example, two social graphs 112 have a similar number of
connections if the number of connections are within twenty-five
percent of one another. Alternative percentages or absolute numbers
of connections may be utilized as appropriate.
[0089] The bonus may be increased the closer in numbers the two
social graphs 112 are. Thus, the bonus may be 0.005 if the social
graphs 112 are within twenty-five percent, 0.003 if the social
graphs are between seventy-five and twenty-five percent, and 0.001
if the social graphs are between seventy-five and one hundred
percent of one another. The bonus may be negative if the social
graphs 112 are larger than a certain percentage. In an example, if
the social graphs 112 are more than two hundred percent of one
another then the penalty may be 0.001, and so forth. It is to be
recognized that the percentages may be from comparing the largest
number of connections with the smallest number of connections for
the purposes of this illustration. Thus, if the connections were
one hundred twenty-five and one hundred then the percentage would
be twenty-five percent. If the connections were two hundred and one
hundred then the percentage would be one hundred percent. If the
connections were three hundred and one hundred then the percentage
would be two hundred percent, and so forth.
[0090] Affinities may be combined with one another to produce
relatively more complex affinities. Thus, in an example, the
content item type affinity may be combined with the network-size
affinity or network size generally. Utility values between various
affinity metrics may be added, multiplied, or otherwise combined
together to provide a broader affinity bonus. The federator module
108 may empirically determine, for instance in the testing mode,
and further correlation between individual affinities and adjust
combined bonuses accordingly. As such, the combination of content
item type affinity and network size may produce a different bonus
depending on how those affinities relate in actual practice.
[0091] The federator module 108 may utilize various techniques to
provide content items 122 in the news feed 400 in a manner that is
financially efficient for the social network as well as useful to
and visually pleasing for the member to whom it is presented. In
particular, the federator module 108 may provide for blending of
content items 122 so that particular types of content items 122 do
not clump or otherwise dominate the news feed 400, notwithstanding
the absolute utility values of those content items 122. Further,
the federator module 108 may provide for diversity of content item
122 type on the news feed 400.
[0092] Blending of content items 122 may utilize the data from the
content item 122 type analysis above to prevent undue clumping of
content items 122 of the same type from occurring. In various
examples, content item types may include sponsored or organic
content, content items provided by the same source, content items
related to the same topic, content items providing the same type of
information (such as members who change jobs or notices that an
entity is "trending", and so forth), and so forth.
[0093] The federator module 108 may utilize the testing mode to
identify degrees of blending, or lack thereof, that promote user
interaction with content items 122 in the news feed 400. The
federator module 108 may empirically determine degrees of blending
according to the same content item types in adjacent positions 402,
a number of the same content item type in consecutive positions
402, a percentage of the same content item type in consecutive
positions 402 (e.g., three content items 122 of the same type in
five consecutive positions 402), and so forth. The federator module
108 may utilize the testing mode to display content items 122
according to their utility values but without respect to blending
concepts and then iteratively apply different blending concepts to
empirically determine blending concepts that provide for optimized
user interaction with content items 122, optimized utility value,
and any of a variety of other metrics.
[0094] In an example, the federator module 108 may operate in the
testing mode to determine blending concepts by testing concepts of
varying stringency. Thus, a blending concept may mandate no content
items 122 of the same type in adjacent positions 402. A less
stringent blending concept may mandate that two content items 122
of the same type may be in adjacent positions 402 but not three,
and so forth. Blending concepts may also be sensitive to certain
types of content items 122 but intentionally not other types. Thus,
in an example, the blending concepts may be sensitive or more
sensitive to certain content item 122 types and not others. By way
of illustration, a first blending concept may require that
sponsored content items 122 not be placed in adjacent positions 402
while a second blending concept, implemented concurrently with the
first blending concept, may require that not more than three
content items 122 provided from the same source be placed in five
consecutive positions 402, and so forth.
[0095] It is to be recognized that certain blending concepts may be
produce results that are inconsistent or conflict with one another,
such as where one concept suggests a placement of a content item
122 in a position 402 but another concept determines that the
content item 122 cannot be placed in that position 402. In cases
such as those, the federator module 108 may establish a hierarchy
for resolving conflicts. In such a hierarchy, one blending concept
may control conflicts. In the above example, the sponsored content
blending concept may override the source blending concept. The
hierarchy, along with the parameters of the blending concepts, may
also be set as a matter of social network policy and may not
necessarily be adjusted by the federator module.
[0096] The federator module 108 may provide for diversity in the
news feed 400 by adjusting utility values or associated positions
402 of content items 122 that are related to content items 122 that
have already been seen by a user on the news feed 400 or will
already have been seen by the user on the news feed 400. Thus, in
various examples, a content item 122 of a content item type with a
highest utility value may be placed in a high position 402. The
federator module 108 may, depending on the diversity criteria,
adjusting the utility values or positions of lower utility value
content items 122 of the content item type to prevent the other
content items 122 of the type from being in positions 402 that are
too close to the position 402 of the highest-value content item
122.
[0097] In an example, four content items 122 of a single content
item type have utility values that would cause those content items
122 to be placed in positions 402 on the news feed 400. The
federator module 108 may then apply a discount to the three content
items 122 having the lowest utility values. In an example, each of
the lowest-value three content items 122 would have their utility
value multiplied by a predetermined factor, such as 0.75, and
reassessed for new positions 402 in the news feed 400. It is noted
that the reassessment of the three content items 122 may result in
other content items 122 of the type being repositioned accordingly.
Thus, if the second-highest-value content item 122 of the type
drops three positions 402 because of the diversity discount, then
the content items 122 in those three positions 402 would each be
moved up by one position 402.
[0098] Upon the application of the discount to the three content
items 122, the federator module 108 may reassess if the diversity
requirements have been met. If not, the discount may be iteratively
applied again to each of the content items 122 of the type that
still violate diversity requirements; in such an example, those
content items 122 that have the discount applied twice would have a
discount of 0.75 2=0.5625. The discount may be iteratively applied
to individual ones of the content items 122 of the type until the
content items 122 of the type meet the diversity requirement.
[0099] The federator module 108 may rank the content items 122 it
assesses according to their utility values and then apply diversity
requirements to all of the content items 122 that have been ranked
or to a predetermined number of the highest ranked content items
122. Diversity requirements may be applied concurrently among all
of the content items 122 that are ranked or to the predetermined
number of the highest ranked content items 122. As the diversity
requirements are applied to the ranked content items 122, the
discounts may be applied to the ranked content items 122 as
appropriate. Thus, content items 122 that violate any of the
diversity requirements may have the discount applied to their
utility values.
[0100] Following the application of the discount to the utility
values of the ranked content items 122, the federator module 108
may re-rank the content items 122 and reassess the content items
122 for the diversity requirements. Content items 122 that, as
re-ranked, violate the diversity requirements may have the discount
applied again and may be re-ranked. The assessment of diversity
requirements, the application of a discount to the utility values
of content items 122 that violate the diversity requirements, and
the re-ranking of content items 122 may be conducted iteratively
until all of the diversity requirements are met, the content items
122 as ranked settle into a steady state, or a "time-out" condition
is met following a predetermined number of iterations.
[0101] The content item 122 types may be based on a variety of
factors and each content item 122 may have multiple item types. In
an example, content items 122 may be classified according to an
actor of the content item 122, such as a user who posted an article
or a user about whom the content item refers. e.g., "John Doe
started a new job at Company X." In an example, content items 122
may be classified according to a verb or action of the content item
122; thus, in the above example, a content item may have as a verb
or action "started a new job". In an example, content items 122 may
be classified according to an object of the content item 122; thus,
in the above example, the object would be "Company X".
[0102] The diversity requirement may be general in the news feed
400 or may be local in the news feed 400. In an example, a local
diversity requirement may require diversity among the positions 402
that are displayed on the news feed 400 at any one time but not for
positions 402 that are not or cannot be displayed concurrent with
the positions 402 that are currently displayed. Thus, in an
example, if the news feed 400 as a whole only displays five
positions 402 at a time then the diversity requirement may only be
applied to the content items 122 that would be displayed in those
five positions 402 based on the initial utility value ranking.
[0103] The federator module 108 may utilize the testing mode to
optimize diversity requirements. The optimization may be generally
applied across the members and users of the social network or may
be individually applied to members based on those member's
responses to various diversity requirement implementations. Thus,
the federator module 108 may randomly vary diversity requirements
and, for instance, allow four content items 122 of the same type
within an eight-position 402 block when the base diversity
requirement is for only three content items 122 of the same type
and assess the reaction of users to the relatively less-diverse
requirement. If the less-diverse requirement produces greater user
interaction with content items in the news feed 400 then the
less-diverse requirement may be implemented as the default
diversity requirement. It is to be recognized that these principles
may be applied to individual members of the social network for
personalized diversity requirements.
Flowchart
[0104] FIG. 6 is a flowchart for ranking adjustment of federated
content items in a social network, in an example embodiment. The
flowchart may be implemented according to any of a variety of
example systems and methods disclosed herein or as may be suitable
for implementing the flowchart.
[0105] At operation 600, content items from a first content item
source are caused to be selectively displayed on a user interface
with a processor, via a network interface, the first content item
source begin stored in an electronic data storage, the content
items form the first content item source being ranked according to
a first ranking schema. In an example, causing the content items of
the first one of the content item sources to be selectively
displayed is by randomly varying positions on the user interface in
which the content items are displayed. In an example, causing the
content items of the first one of the content item sources to be
selectively displayed is by systematically varying positions on the
user interface in which the content items are displayed. In an
example, causing the content items of the first one of the content
item sources to be selectively displayed is based on the associated
one of the ranking schemas as unadjusted.
[0106] At operation 602, content items from a second content item
source, from the electronic data storage, are caused to be
displayed on the user interface with the processor, via the network
interface, based, at least in part, on a ranking according to a
second ranking schema associated with the second content item
source.
[0107] At operation 604, activity data related to interactions with
the content items from the first content item source are obtained
with the processor.
[0108] At operation 606, a utility value is computed individually,
for each of the content items of the first content item source,
based on the first ranking schema and the utility value
adjustment.
[0109] At operation 608, content items from the second content item
source are caused, by the processor, via the network interface, to
be selectively displayed on a user interface.
[0110] At operation 610, activity data related to interactions with
the content items from the second content item source are obtained
with the processor.
[0111] At operation 612, the utility value is computed
individually, for each of the content items of the second content
item source, based, at least in part, on the second ranking schema.
In an example, computing individually the utility value for the
content items of the second content item source further based on a
second utility value adjustment for the second content item source.
In an example, the second utility value adjustment is determined
based on the activity data.
[0112] At operation 614, a utility value adjustment to be applied
to the first ranking schema is determined by the processor based on
the activity data. In an example, determining the utility value
adjustment based on a variation of the activity data from an
expected interaction rate. In an example, the utility value
adjustment is a percentage difference between a rate at which the
activity data shows interactions with the content items and the
expected interaction rate.
[0113] At operation 616, content items from the first and second
content item sources are caused to be displayed on the user
interface by the processor, via the network interface, content
items of the first content item source being displayed according to
the utility value adjustment and the first ranking schema and the
content items of the second content item source being displayed
based, at least in part, on the second ranking schema. In an
example, causing the content items to be displayed is according to
their respective utility values. In an example, causing the content
items of the first and second content item sources to be displayed
on the user interface is in positions according to their utility
values as individually computed.
System
[0114] FIG. 7 is a block diagram illustrating components of a
machine 700, according to some example embodiments, able to read
instructions from a machine-readable medium (e.g., a
machine-readable storage medium) and perform any one or more of the
methodologies discussed herein. Specifically, the machine 700 may
implement the social network system 100 and the features included
and described therein. The machine 700 thus describes specific
hardware configurations on which the social network system 100 may
be implemented and provided to users of the social network system
100.
[0115] FIG. 7 shows a diagrammatic representation of the machine
700 in the example form of a computer system and within which
instructions 724 (e.g., software) for causing the machine 700 to
perform any one or more of the methodologies discussed herein may
be executed. In alternative embodiments, the machine 700 operates
as a standalone device or may be connected (e.g., networked) to
other machines. In a networked deployment, the machine 700 may
operate in the capacity of a server machine or a client machine in
a server-client network environment, or as a peer machine in a
peer-to-peer (or distributed) network environment. The machine 700
may be a server computer, a client computer, a personal computer
(PC), a tablet computer, a laptop computer, a netbook, a set-top
box (STB), a personal digital assistant (PDA), a cellular
telephone, a smartphone, a web appliance, a network router, a
network switch, a network bridge, or any machine capable of
executing the instructions 724, sequentially or otherwise, that
specify actions to be taken by that machine. Further, while only a
single machine is illustrated, the term "machine" shall also be
taken to include a collection of machines that individually or
jointly execute the instructions 724 to perform any one or more of
the methodologies discussed herein.
[0116] The machine 700 includes a processor 702 (e.g., a central
processing unit (CPU), a graphics processing unit (GPU), a digital
signal processor (DSP), an application specific integrated circuit
(ASIC), a radio-frequency integrated circuit (RFIC), or any
suitable combination thereof), a main memory 704, and a static
memory 706, which are configured to communicate with each other via
a bus 708. The machine 700 may further include a graphics display
710 (e.g., a plasma display panel (PDP), a light emitting diode
(LED) display, a liquid crystal display (LCD), a projector, or a
cathode ray tube (CRT)). The machine 700 may also include an
alphanumeric input device 712 (e.g., a keyboard), a cursor control
device 714 (e.g., a mouse, a touchpad, a trackball, a joystick, a
motion sensor, or other pointing instrument), a storage unit 716, a
signal generation device 718 (e.g., a speaker), and a network
interface device 720.
[0117] The storage unit 716 includes a machine-readable medium 722
on which is stored the instructions 724 (e.g., software) embodying
any one or more of the methodologies or functions described herein.
The instructions 724 may also reside, completely or at least
partially, within the main memory 704, within the processor 702
(e.g., within the processor's cache memory), or both, during
execution thereof by the machine 700. Accordingly, the main memory
704 and the processor 702 may be considered as machine-readable
media. The instructions 724 may be transmitted or received over a
network 726 via the network interface device 720.
[0118] As used herein, the term "memory" refers to a
machine-readable medium able to store data temporarily or
permanently and may be taken to include, but not be limited to,
random-access memory (RAM), read-only memory (ROM), buffer memory,
flash memory, and cache memory. While the machine-readable medium
722 is shown in an example embodiment to be a single medium, the
term "machine-readable medium" should be taken to include a single
medium or multiple media (e.g., a centralized or distributed
database, or associated caches and servers) able to store
instructions. The term "machine-readable medium" shall also be
taken to include any medium, or combination of multiple media, that
is capable of storing instructions (e.g., software) for execution
by a machine (e.g., machine 700), such that the instructions, when
executed by one or more processors of the machine (e.g., processor
702), cause the machine to perform any one or more of the
methodologies described herein. Accordingly, a "machine-readable
medium" refers to a single storage apparatus or device, as well as
"cloud-based" storage systems or storage networks that include
multiple storage apparatus or devices. The term "machine-readable
medium" shall accordingly be taken to include, but not be limited
to, one or more data repositories in the form of a solid-state
memory, an optical medium, a magnetic medium, or any suitable
combination thereof.
[0119] Throughout this specification, plural instances may
implement components, operations, or structures described as a
single instance. Although individual operations of one or more
methods are illustrated and described as separate operations, one
or more of the individual operations may be performed concurrently,
and nothing requires that the operations be performed in the order
illustrated. Structures and functionality presented as separate
components in example configurations may be implemented as a
combined structure or component. Similarly, structures and
functionality presented as a single component may be implemented as
separate components. These and other variations, modifications,
additions, and improvements fall within the scope of the subject
matter herein.
[0120] Certain embodiments are described herein as including logic
or a number of components, modules, or mechanisms. Modules may
constitute either software modules (e.g., code embodied on a
machine-readable medium or in a transmission signal) or hardware
modules. A "hardware module" is a tangible unit capable of
performing certain operations and may be configured or arranged in
a certain physical manner. In various example embodiments, one or
more computer systems (e.g., a standalone computer system, a client
computer system, or a server computer system) or one or more
hardware modules of a computer system (e.g., a processor or a group
of processors) may be configured by software (e.g., an application
or application portion) as a hardware module that operates to
perform certain operations as described herein.
[0121] In some embodiments, a hardware module may be implemented
mechanically, electronically, or any suitable combination thereof.
For example, a hardware module may include dedicated circuitry or
logic that is permanently configured to perform certain operations.
For example, a hardware module may be a special-purpose processor,
such as a field programmable gate array (FPGA) or an ASIC. A
hardware module may also include programmable logic or circuitry
that is temporarily configured by software to perform certain
operations. For example, a hardware module may include software
encompassed within a general-purpose processor or other
programmable processor. It will be appreciated that the decision to
implement a hardware module mechanically, in dedicated and
permanently configured circuitry, or in temporarily configured
circuitry (e.g., configured by software) may be driven by cost and
time considerations.
[0122] Accordingly, the phrase "hardware module" should be
understood to encompass a tangible entity, be that an entity that
is physically constructed, permanently configured (e.g.,
hardwired), or temporarily configured (e.g., programmed) to operate
in a certain manner or to perform certain operations described
herein. As used herein, "hardware-implemented module" refers to a
hardware module. Considering embodiments in which hardware modules
are temporarily configured (e.g., programmed), each of the hardware
modules need not be configured or instantiated at any one instance
in time. For example, where a hardware module comprises a
general-purpose processor configured by software to become a
special-purpose processor, the general-purpose processor may be
configured as respectively different special-purpose processors
(e.g., comprising different hardware modules) at different times.
Software may accordingly configure a processor, for example, to
constitute a particular hardware module at one instance of time and
to constitute a different hardware module at a different instance
of time.
[0123] Hardware modules can provide information to, and receive
information from, other hardware modules. Accordingly, the
described hardware modules may be regarded as being communicatively
coupled. Where multiple hardware modules exist contemporaneously,
communications may be achieved through signal transmission (e.g.,
over appropriate circuits and buses) between or among two or more
of the hardware modules. In embodiments in which multiple hardware
modules are configured or instantiated at different times,
communications between such hardware modules may be achieved, for
example, through the storage and retrieval of information in memory
structures to which the multiple hardware modules have access. For
example, one hardware module may perform an operation and store the
output of that operation in a memory device to which it is
communicatively coupled. A further hardware module may then, at a
later time, access the memory device to retrieve and process the
stored output. Hardware modules may also initiate communications
with input or output devices, and can operate on a resource (e.g.,
a collection of information).
[0124] The various operations of example methods described herein
may be performed, at least partially, by one or more processors
that are temporarily configured (e.g., by software) or permanently
configured to perform the relevant operations. Whether temporarily
or permanently configured, such processors may constitute
processor-implemented modules that operate to perform one or more
operations or functions described herein. As used herein,
"processor-implemented module" refers to a hardware module
implemented using one or more processors.
[0125] Similarly, the methods described herein may be at least
partially processor-implemented, a processor being an example of
hardware. For example, at least some of the operations of a method
may be performed by one or more processors or processor-implemented
modules. Moreover, the one or more processors may also operate to
support performance of the relevant operations in a "cloud
computing" environment or as a "software as a service" (SaaS). For
example, at least some of the operations may be performed by a
group of computers (as examples of machines including processors),
with these operations being accessible via a network (e.g., the
Internet) and via one or more appropriate interfaces (e.g., an
application program interface (API)).
[0126] The performance of certain of the operations may be
distributed among the one or more processors, not only residing
within a single machine, but deployed across a number of machines.
In some example embodiments, the one or more processors or
processor-implemented modules may be located in a single geographic
location (e.g., within a home environment, an office environment,
or a server farm). In other example embodiments, the one or more
processors or processor-implemented modules may be distributed
across a number of geographic locations.
[0127] Some portions of this specification are presented in terms
of algorithms or symbolic representations of operations on data
stored as bits or binary digital signals within a machine memory
(e.g., a computer memory). These algorithms or symbolic
representations are examples of techniques used by those of
ordinary skill in the data processing arts to convey the substance
of their work to others skilled in the art. As used herein, an
"algorithm" is a self-consistent sequence of operations or similar
processing leading to a desired result. In this context, algorithms
and operations involve physical manipulation of physical
quantities. Typically, but not necessarily, such quantities may
take the form of electrical, magnetic, or optical signals capable
of being stored, accessed, transferred, combined, compared, or
otherwise manipulated by a machine. It is convenient at times,
principally for reasons of common usage, to refer to such signals
using words such as "data," "content," "bits," "values,"
"elements," "symbols," "characters," "terms," "numbers,"
"numerals," or the like. These words, however, are merely
convenient labels and are to be associated with appropriate
physical quantities.
[0128] Unless specifically stated otherwise, discussions herein
using words such as "processing," "computing," "calculating,"
"determining," "presenting," "displaying," or the like may refer to
actions or processes of a machine (e.g., a computer) that
manipulates or transforms data represented as physical (e.g.,
electronic, magnetic, or optical) quantities within one or more
memories (e.g., volatile memory, non-volatile memory, or any
suitable combination thereof), registers, or other machine
components that receive, store, transmit, or display information.
Furthermore, unless specifically stated otherwise, the terms "a" or
"an" are herein used, as is common in patent documents, to include
one or more than one instance. Finally, as used herein, the
conjunction "or" refers to a non-exclusive "or," unless
specifically stated otherwise.
* * * * *