U.S. patent application number 17/171770 was filed with the patent office on 2021-09-02 for generating and presenting targeted advertisements including representations of subject individuals.
The applicant listed for this patent is LIVINGSOCIAL, INC.. Invention is credited to David Robert Gentzel, Sourabh Niyogi.
Application Number | 20210271721 17/171770 |
Document ID | / |
Family ID | 1000005594742 |
Filed Date | 2021-09-02 |
United States Patent
Application |
20210271721 |
Kind Code |
A1 |
Niyogi; Sourabh ; et
al. |
September 2, 2021 |
GENERATING AND PRESENTING TARGETED ADVERTISEMENTS INCLUDING
REPRESENTATIONS OF SUBJECT INDIVIDUALS
Abstract
Advertisements are generated and selected for display to users,
wherein the advertisements include representations of subject
individuals. These subject individuals can be friends with whom the
user interacts on the Internet and/or any other contributors who
may or may not have expertise with regard to the subject matter of
the advertisement. A subject individual can be portrayed in an
advertisement by including any type of representation of the
individual. Ranks for the subject individuals are determined based
on the subject individuals' interactions with advertisements and/or
on other factors. An advertisement is selected and presented to a
user based on a score derived from friends' and/or contributors'
interactions with the advertisement. According to various
embodiments of the invention, a method is provided for choosing
which advertisement(s) to show to a user and which subject
individuals to portray in the advertisements.
Inventors: |
Niyogi; Sourabh;
(Burlingame, CA) ; Gentzel; David Robert; (Mill
Valley, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
LIVINGSOCIAL, INC. |
WASHINGTON |
DC |
US |
|
|
Family ID: |
1000005594742 |
Appl. No.: |
17/171770 |
Filed: |
February 9, 2021 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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12393795 |
Feb 26, 2009 |
10949485 |
|
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17171770 |
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61031692 |
Feb 26, 2008 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06Q 10/00 20130101;
G06F 16/955 20190101; G06F 16/24578 20190101; G06Q 30/00 20130101;
G06Q 30/0255 20130101; G06Q 30/0269 20130101 |
International
Class: |
G06F 16/955 20060101
G06F016/955; G06F 16/2457 20060101 G06F016/2457; G06Q 10/00
20060101 G06Q010/00; G06Q 30/00 20060101 G06Q030/00; G06Q 30/02
20060101 G06Q030/02 |
Claims
1-38. (canceled)
39. A computer-implemented method for selecting and presenting one
or more advertisements to a user, comprising: receiving, via an
interaction receiving engine, and recording, at a server, one or
more indications of advertisement interactions, the one or more
indications of advertisement interactions being received input at a
client device associated with the user and indicative of activity
between the client device and one or more presented advertisements
that are displayed on the client device; receiving and storing, at
an interaction database, metadata corresponding to one or more
indications of social network interactions occurring between the
client device associated with the user and at least one interacting
subject individual using an Internet-based social network, wherein
the metadata corresponding to each of the one or more indications
of social network interactions is stored in a uniform format so as
to enable comparison of the one or more indications of social
network interactions to which the metadata corresponds; receiving,
at the server from the client device associated with the user, a
request for the one or more presented advertisements to be
presented to the user; for each of a plurality of candidate
advertisements, determining, by the server, (i) at least one friend
rank comprising a metric associated with the at least one
interacting subject individual with whom the user has interacted
using the Internet-based social network, wherein the at least one
friend rank is determined at least in part by the received and
stored metadata and (ii) at least one contributor rank indicating
relative performance of advertisements containing a representation
of a contributing subject individual, the at least one contributor
rank not being based on social network interactions between the
contributing subject individual and the user; for each of the
plurality of candidate advertisements, aggregating the at least one
friend rank and the at least one contributor rank, and generating a
score for each of the plurality of candidate advertisements based
at least in part on the aggregated at least one friend rank and the
at least one contributor rank, with the score differing from the at
least one friend rank and the at least one contributor rank;
identifying a selected advertisement set from the plurality of
candidate advertisements based at least in part on the generated
scores; selecting, from the selected advertisement set, the one or
more presented advertisements based on one or more presentation
criteria; comparing at least one normalized contributor rank for
the one or more presented advertisements to at least one normalized
friend rank for the one or more presented advertisements;
selecting, based on the comparing, a represented subject
individual, the represented subject individual having contributed
input with respect to the subject matter of the one or more
presented advertisements and having at least one recorded
indication of an interaction with the one or more presented
advertisements; determining a representation type placeholder in
the one or more presented advertisements; obtaining, from a storage
database by the server, a representation of the represented subject
individual having a representation type that matches the
representation type placeholder; configuring, by the server, the
one or more presented advertisements to include the representation
of the represented subject individual, obtained from the storage
database, inserted at the representation type placeholder in the
one or more presented advertisements; electronically transmitting
visible indicia of the one or more presented advertisements to a
user interface of a display of the client device associated with
the user, wherein, in response to receiving the one or more
presented advertisements, the client device associated with the
user is configured to display, via the display of the client device
associated with the user, the one or more presented advertisements
that comprises the representation of the represented subject
individual and enables user interaction by the user, via the user
interface, with the visible indicia associated with the one or more
presented advertisements; and detecting, via the user interface,
and storing an interaction of the user with the visible indicia of
the one or more presented advertisements that comprises the
representation of the represented subject individual.
40. The method of claim 1, wherein the one or more presentation
criteria include a pre-defined rotation, a random selection, and a
ranking within the selected advertisement set.
41. The method of claim 1, wherein the representation of the
represented subject individual comprises at least one selected from
the group consisting of: a picture of the represented subject
individual; a name of the represented subject individual; an icon
representing the represented subject individual; and an identifier
for the represented subject individual.
42. The method of claim 1, wherein identifying the selected
advertisement set based at least in part on the generated scores
comprises identifying one or more selected advertisements of the
selected advertisement set that each have a generated score
exceeding a threshold.
43. The method of claim 1, wherein the at least one friend rank
comprises a friend rank associated with the at least one
interacting subject individual with whom the user has interacted on
an electronically implemented social network.
44. The method of claim 1, wherein the at least one friend rank
comprises a friend rank indicating a degree of interaction between
the user and the at least one interacting subject individual with
whom the user has interacted.
45. The method of claim 1, wherein the at least one friend rank
comprises a friend rank generated responsive to at least one
interaction between the at least one interacting subject individual
with whom the user has interacted and an Internet-based component
associated with the one or more presented advertisements.
46. The method of claim 1, wherein the representation of the
represented subject individual comprises an indication of the
represented subject individual's previous interaction with an
advertisement.
47. The method of claim 1, wherein the one or more presented
advertisements are output as a component of a web page display.
48. The method of claim 1, wherein at least one of the one or more
presented advertisements comprises at least one selected from the
group consisting of: an audio advertisement; an animated
advertisement; a video; a text based advertisement; a text message;
an instant message; an email message; a web page; a banner; and a
portion of a web page.
49. The method of claim 1, further comprising: receiving the user's
interactions with the one or more presented advertisements; and
storing the user's interactions in a storage medium.
50. The method of claim 1, wherein generating the score based at
least in part on the aggregated at least one friend rank and the at
least one contributor rank comprises generating the score based on
the aggregated at least one friend rank and the at least one
contributor rank combined with a user score based on the user's
history of interactions on the Internet.
51. A computer program product for selecting and presenting an
advertisement to a user, comprising: a computer-readable storage
medium; and computer program code, encoded on the computer-readable
storage medium, for causing an electronic device to perform the
steps of: receiving, via an interaction receiving engine, and
recording, at a server, one or more indications of advertisement
interactions, the one or more indications of advertisement
interactions being received input at a client device associated
with the user and indicative of activity between the client device
and one or more presented advertisements that are displayed on the
client device; receiving and storing, at an interaction database,
metadata corresponding to one or more indications of social network
interactions occurring between the client device associated with
the user and at least one interacting subject individual using an
Internet-based social network, wherein the metadata corresponding
to each of the one or more indications of social network
interactions is stored in a uniform format so as to enable
comparison of the one or more indications of social network
interactions to which the metadata corresponds; receiving, at the
server from the client device associated with the user, a request
for the one or more presented advertisements to be presented to the
user; for each of a plurality of candidate advertisements,
determining, by the server, (i) at least one friend rank comprising
a metric associated with the at least one interacting subject
individual with whom the user has interacted using the
Internet-based social network, wherein the at least one friend rank
is determined at least in part by the received and stored metadata
and (ii) at least one contributor rank indicating relative
performance of advertisements containing a representation of a
contributing subject individual, the at least one contributor rank
not being based on social network interactions between the
contributing subject individual and the user; for each of the
plurality of candidate advertisements, aggregating the at least one
friend rank and the at least one contributor rank, and generating a
score for each of the plurality of candidate advertisements based
at least in part on the aggregated at least one friend rank and the
at least one contributor rank, with the score differing from the at
least one friend rank and the at least one contributor rank;
identifying a selected advertisement set from the plurality of
candidate advertisements based at least in part on the generated
scores; selecting, from the selected advertisement set, the one or
more presented advertisements based on one or more presentation
criteria; comparing at least one normalized contributor rank for
the one or more presented advertisements to at least one normalized
friend rank for the one or more presented advertisements;
selecting, based on the comparing, a represented subject
individual, the represented subject individual having contributed
input with respect to the subject matter of the one or more
presented advertisements and having at least one recorded
indication of an interaction with the one or more presented
advertisements; determining a representation type placeholder in
the one or more presented advertisements; obtaining, from a storage
database by the server, a representation of the represented subject
individual having a representation type that matches the
representation type placeholder; configuring, by the server, the
one or more presented advertisements to include the representation
of the represented subject individual, obtained from the storage
database, inserted at the representation type placeholder in the
one or more presented advertisements; electronically transmitting
visible indicia of the one or more presented advertisements to a
user interface of a display of the client device associated with
the user, wherein, in response to receiving the one or more
presented advertisements, the client device associated with the
user is configured to display, via the display of the client device
associated with the user, the one or more presented advertisements
that comprise the representation of the represented subject
individual and enable user interaction by the user, via the user
interface, with the visible indicia associated with the one or more
presented advertisements; and detecting, via the user interface,
and storing an interaction of the user with the visible indicia of
the one or more presented advertisements that comprise the
representation of the represented subject individual.
52. The computer program product of claim 13, wherein the one or
more presentation criteria include a pre-defined rotation, a random
selection, and a ranking within the selected advertisement set.
53. The computer program product of claim 13, wherein the at least
one friend rank comprises a friend rank associated with the at
least one interacting subject individual with whom the user has
interacted on an electronically implemented social network.
54. The computer program product of claim 13, wherein the at least
one friend rank comprises a friend rank indicating a degree of
interaction between the user and the at least one interacting
subject individual with whom the user has interacted.
55. The computer program product of claim 13, wherein the at least
one friend rank comprises a friend rank generated responsive to at
least one interaction between the at least one interacting subject
individual with whom the user has interacted and an Internet-based
component associated with the advertisement.
56. The computer program product of claim 13, wherein at least one
of the one or more presented advertisements comprises at least one
selected from the group consisting of: an audio advertisement; an
animated advertisement; a video; a text based advertisement; a text
message; an instant message; an email message; a web page; a
banner; and a portion of a web page.
57. The computer program product of claim 13, comprising further
computer program code for: receiving the user's interactions with
the one or more presented advertisements; and storing the user's
interactions in a storage medium.
58. A system for selecting and presenting an advertisement to a
user, comprising: an interaction receiving engine to receive one or
more indications of advertisement interactions; a database to
record the one or more indications of advertisement interactions,
indications of advertisement interactions being received input at a
client device associated with a user indicative of activity between
the client device associated with the user and one or more
presented advertisements displayed on the client device associated
with the user; an interaction database to receive and record
metadata corresponding to one or more indications of social network
interactions occurring between the client device associated with
the user and at least one interacting subject individual using an
Internet-based social network, wherein the metadata corresponding
to each of the one or more indications of social network
interactions is stored in a uniform format so as to enable
comparison of the one or more indications of social network
interactions to which the metadata corresponds; a server, to
receive, from the client device associated with the user, a request
for the one or more presented advertisements to be presented to the
user; an advertisement rank computation and selection engine to:
for each of a plurality of candidate advertisements, determine (i)
at least one friend rank comprising a metric associated with the at
least one interacting subject individual with whom the user has
interacted using the Internet-based social network, wherein the at
least one friend rank is determined at least in part by the
received and stored metadata and (ii) at least one contributor rank
indicating relative performance of advertisements containing a
representation of a contributing subject individual, the at least
one contributor rank not being based on social network interactions
between the contributing subject individual and the user; for each
of the plurality of candidate advertisements, aggregate the at
least one friend rank and the at least one contributor rank, and
generate a score for each of the plurality of candidate
advertisements based at least in part on the aggregated at least
one friend rank and the at least one contributor rank, with the
score differing from the at least one friend rank and the at least
one contributor rank; identify a selected advertisement set from
the plurality of candidate advertisements based at least in part on
the generated scores; select, from the selected advertisement set,
the one or more presented advertisements based on one or more
presentation criteria; compare at least one normalized contributor
rank for the one or more presented advertisements to at least one
normalized friend rank for the one or more presented
advertisements; select, based on the comparing, a represented
subject individual, the represented subject individual having
contributed input with respect to the subject matter of the one or
more presented advertisements and having at least one recorded
indication of an interaction with the one or more presented
advertisements; determine a representation type placeholder in each
of the one or more presented advertisements; obtain, from a storage
database by the server, a representation of the represented subject
individual having a representation type that matches each of the
representation type placeholders in the one or more presented
advertisements; configure, by the server, the one or more presented
advertisements to include the representation of the represented
subject individual, obtained from the storage database, inserted at
each of the representation type placeholders in the one or more
presented advertisements; a transmission device to electronically
transmit visible indicia of the one or more presented
advertisements to a user interface of a display of the client
device associated with the user, wherein, in response to receiving
the one or more presented advertisements, the client device
associated with the user is configured to display, via the display,
the one or more presented advertisements that comprise the
representation of the represented subject individual; and detect,
via the user interface, and store an interaction of the user with
the one or more presented advertisements that comprise the
representation of the represented subject individual.
Description
CROSS-REFERENCES TO RELATED APPLICATIONS
[0001] This application claims priority from U.S. Provisional
Application Ser. No. 61/031,692, for "Targeting Advertising Using
Data Captured by Social Networks", filed on Feb. 26, 2008, which is
incorporated herein by reference.
[0002] This application is related to U.S. Utility patent
application Ser. No. 12/277,237 for "Ranking Interactions Between
Users on the Internet", filed Nov. 24, 2008, which is incorporated
herein by reference.
FIELD OF ART
[0003] The present disclosure is directed to generating and
presenting targeted advertisements to users of the web, wherein
such advertisements include representations of subject
individuals.
DESCRIPTION OF RELATED ART
[0004] With the changing trend in the use of World Wide Web
technology that aims to enhance creativity, information sharing,
and, most notably, collaboration among users, there has been an
evolution of web-based communities and hosted services in the form
of social media. "Social media" is an umbrella term for activities
that enable people to interlink and interact with engaging content
in a conversational and participatory manner via the Internet. In
essence, social media is used to describe how people socialize or
interact with each other throughout the World Wide Web.
[0005] Social media includes, for example, social networks where
users build profiles and friend lists, photo sharing websites,
instant messaging applications, web-based email, retail sites where
users can share wish lists, wedding planning sites that allow users
to create personalized pages to share information about a wedding
with guests, and combinations of several of these. Some social
media, including social networks, have created open platforms so
that external developers can write applications that use data
captured by social media. Often, these applications correspond to
advertising applications that provide for monetization of social
media.
[0006] Advertising on the Internet generally attempts to maximize
the effective cost per thousand impressions (eCPM). eCPM is a
well-known measurement of advertising effectiveness that indicates
how much each thousand units of an advertisement inventory costs an
advertiser. The ranks of advertisements are computed by multiplying
bid eCPM's by user scores (also referred to as quality scores). The
advertisements with the highest ad rank are given preferential
treatment. In the case of advertising opportunities where only one
advertisement is displayed, preferential treatment means
higher-ranked advertisements are displayed more often than
lower-ranked advertisements. In a situation where multiple
advertisements are displayed, preferential treatment means the
advertisement is displayed more prominently than the others.
SUMMARY
[0007] According to various embodiments of the present invention,
advertisements are generated and displayed to a user, wherein the
advertisements portray other individuals, including friends with
whom the user has interacted on the Internet and/or other
contributors whom the user is likely to trust or pay attention to
even if the user has not directly interacted with them. In the
context of the present disclosure, a "friend" is an individual with
whom the user interacts or has interacted, while a "contributor" is
an individual that the user may not necessarily have interacted
with. Contributors can include, for example, experts that have
particular qualifications that render them trustworthy or
well-respected with regard to particular subject matter, and/or any
other individuals that have an opinion or other input they wish to
share about the subject matter. Friends and contributors are
referred to herein as "subject individuals". According to
techniques described herein, subject individuals can be portrayed
in advertisements presented to users. A subject individual need not
have explicitly or implicitly referred an advertisement to a target
user. A subject individual can be portrayed in an advertisement by
including any type of representation of the subject individual,
including representations that are visual, animated, text-based,
numeric, icon-based, or of any other type; such representations can
include a name, user ID, sketch, icon, handle, or any other
indicator of the subject individual's identity, whether a fictional
identity or an actual identity.
[0008] Advertisements are selected and/or generated based, in part,
on a rank, or score, for subject individuals that are relevant to
the user to whom the advertisement is targeted (the "target
user").
[0009] In various embodiments, advertisements can be selected and
presented to the target user based on any of a number of factors,
taken alone or in combination. Such factors can include, for
example: previous interactions of subject individuals relevant to
the target user, where such previous interactions can take place
directly with or in the advertisement; and/or other actions taken
by subject individuals relevant to the target user, such as
contributing related content in an environment other than an
advertisement.
[0010] Conversely, the selection of advertisements for presentation
to the user can be viewed as a process of eliminating some
advertisements from a set of candidate advertisements. For example,
it may be appropriate in some cases to eliminate an advertisement
if no subject individuals have interacted with the advertisement.
Similarly, it may be appropriate in some cases to eliminate an
advertisement if no friends of the target user have interacted or
contributed with the advertisement.
[0011] Once an advertisement has been selected for display to the
target user, a particular subject individual (or more than one) is
selected to be portrayed in the advertisement. Selection of subject
individual can be based on various factors, including for example
the target user's interaction history with subject individuals, a
degree of authoritativeness of the subject individual with respect
to the subject matter of the advertisement (based, for example, on
expertise, actions, contributions, and/or contributed content),
popularity of the subject individual, and potentially other
factors.
[0012] Thus, according to various embodiments of the invention, a
method is provided for choosing which advertisement(s) to show to a
user and for selecting individuals to portray in the
advertisements.
[0013] In one example, a contributor can be any individual who has
submitted a review or opinion, whether or not the individual has
any particular expertise on the subject of the review or opinion.
In another example, a contributor can be an individual who has
donated to a particular cause, so that the fact that the individual
has donated may potentially influence other users to donate to the
same cause. In general, the contributor can be any individual whose
action, comment, submission, or other contribution might
potentially influence the actions of other users, regardless of the
actual merit or quality of the individual's action, comment,
submission, or other contribution, and regardless of whether the
contributor has any objective expertise on the relevant
subject.
[0014] In this manner, the present invention provides a mechanism
for presenting advertisements that the target user is more likely
to act on, and/or for delivering a message that is inherently more
relevant or valuable regardless of whether the target user acts,
particularly since the advertisement includes a representation of a
friend and/or relevant contributor.
[0015] Accordingly, using data from interactions among users via
social media, the techniques described herein allow advertising
networks to improve their web advertising display and advertising
selection processes to show more engaging social advertising to
users, and thereby increase the effectiveness of advertising
efforts.
[0016] The features and advantages described in the specification
are not all inclusive and, in particular, many additional features
and advantages will be apparent to one of ordinary skill in the art
in view of the drawings, specification, and claims. Moreover, it
should be noted that the language used in the specification has
been principally selected for readability and instructional
purposes, and may not have been selected to delineate or
circumscribe the disclosed subject matter.
BRIEF DESCRIPTION OF THE DRAWINGS
[0017] The disclosed embodiments have other advantages and features
which will be more readily apparent from the detailed description,
the appended claims, and the accompanying figures (or drawings). A
brief introduction of the figures is below.
[0018] FIG. 1 illustrates a system architecture according to one
embodiment.
[0019] FIG. 2 illustrates one embodiment of a computer for
implementing the present invention according to one embodiment.
[0020] FIG. 3A illustrates a screenshot of a user interface
displaying an advertisement to a first user according to one
embodiment.
[0021] FIG. 3B illustrates a screenshot of a user interface
displaying the interface after the first user has interacted with
the advertisement, according to one embodiment.
[0022] FIG. 3C illustrates a screenshot of a user interface
displaying the advertiser's site as it appears after the first user
has clicked through the advertisement, according to one
embodiment.
[0023] FIG. 3D illustrates a screenshot of a user interface
displaying to a second user an advertisement portraying the first
user, according to one embodiment.
[0024] FIG. 3E illustrates a screenshot of a user interface
displaying the interface after the second user has interacted with
the advertisement, according to one embodiment.
[0025] FIG. 4 is a flow diagram depicting a method for displaying
an advertisement to a user according to one embodiment
DETAILED DESCRIPTION
[0026] The figures and the following description relate to
preferred embodiments by way of illustration only. It should be
noted that from the following discussion, alternative embodiments
of the structures and methods disclosed herein will be readily
recognized as viable alternatives that may be employed without
departing from the principles of what is claimable subject
matter.
[0027] Reference will now be made in detail to several embodiments,
examples of which are illustrated in the accompanying figures. It
is noted that wherever practicable similar or like reference
numbers may be used in the figures and may indicate similar or like
functionality. The figures depict embodiments of the disclosed
system (or method) for purposes of illustration only. One skilled
in the art will readily recognize from the following description
that alternative embodiments of the structures and methods
illustrated herein may be employed without departing from the
principles described herein.
System Architecture
[0028] FIG. 1 is a depiction of a system architecture and process
flow according to one embodiment. The system comprises a client 110
and a server 100 which communicate with one another via the network
105. The server 100 comprises a log database 115, log analysis
engine 120, user score database 125, response database 130, rank
database 135, interaction database 140, friend rank analysis engine
145, advertisement ("ad") database 150, ad rank computation and
selection engine 155, and an interaction receiving engine 165.
[0029] In one embodiment, the server 100 is implemented as server
program executing on one or more server-class computers comprising
a CPU, memory, network interface, peripheral interfaces, and other
well known components. If more than one computer is present, they
are communicatively coupled together. The computers themselves have
generally high performance CPUs, with 1 GB or more of memory, and
100 GB or more of disk storage. Of course, other types of computers
can be used, and it is expected that as more powerful computers are
developed in the future, they can be configured in accordance with
the teachings here. The functionality implemented by any of the
elements can be provided from computer program products that are
stored in tangible computer readable storage mediums (e.g., RAM,
hard disk, or optical/magnetic media), or by equivalent
implementations in hardware and/or firmware. Alternatively, the
server 100 can be implemented in dedicated hardware, using
custom-designed circuitry to implement the logic of the operations
described herein.
[0030] FIG. 2 illustrates one embodiment of a computer on which the
server 100 can be implemented. Illustrated are at least one
processor 202 coupled to a chipset 204. Also coupled to the chipset
204 are a memory 206, a storage device 208, a keyboard 210, a
graphics adapter 212, a pointing device 214, and a network adapter
216. A display 218 is coupled to the graphics adapter 212. In one
embodiment, the functionality of the chipset 204 is provided by a
memory controller hub 220 and an I/O controller hub 222. In another
embodiment, the memory 206 is coupled directly to the processor 202
instead of the chipset 204.
[0031] The storage device 208 is any device capable of holding
data, for example, a hard drive, compact disk read-only memory
(CD-ROM), DVD, or a solid-state memory device. The memory 206 holds
instructions and data used by the processor 202. The pointing
device 214 may be a mouse, track ball, or other type of pointing
device, and is used in combination with the keyboard 210 to input
data into the computer 200. The graphics adapter 212 displays
images and other information on the display 218. The network
adapter 216 couples the computer 200 to a local or wide area
network.
[0032] As is known in the art, a computer 200 can have different
and/or other components than those shown in FIG. 2. In addition,
the computer 200 can lack certain illustrated components. In one
embodiment, a computer 200 lacks a keyboard 210, pointing device
214, graphics adapter 212, and/or display 218. Moreover, the
storage device 208 can be local and/or remote from the computer 200
(such as embodied within a storage area network (SAN)).
[0033] As is known in the art, the computer 200 is adapted to
execute computer program engines (or modules) for providing
functionality described herein. As used herein, the term "engine"
refers to computer program logic, running on the computer 200,
utilized to provide the specified functionality. Thus, an engine
can be implemented in hardware, firmware, and/or software. In one
embodiment, program engines, such as the log analysis engine 120,
friend rank analysis engine 145, ad rank computation and selection
engine 155 and interaction receiving engine 165 are stored on the
storage device 208, loaded into the memory 206, and executed by the
processor 202.
[0034] Embodiments of the entities described herein can include
other and/or different engines than the ones described here. In
addition, the functionality attributed to the engines can be
performed by other or different engines in other embodiments.
Moreover, this description occasionally omits the term "engine" for
purposes of clarity and convenience.
[0035] In one embodiment, the client 110 is a browser running on a
computing device. The browser can be any browser known in the art,
for example, Microsoft Internet Explorer.TM. or Mozilla
Firefox.TM.. The computing device is any computing device, such as
a personal computer, a notebook computer, or a mobile device such
as a smart phone or personal digital assistant. For simplicity and
ease of discussion, only one client 110 is shown. It is noted
however, that the disclosed configuration functions with numerous
clients 110 communicating with the server 100. The network 105 is
any network, wired or wireless known in the art.
[0036] The log database 115 stores user histories including
representations of users' interactions on the Internet.
Interactions can include interactions with other users as well as
interactions with applications. Examples of interactions with
applications include running a search query at a search engine,
making a purchase at an on-line retailer, and/or interactions
related to an advertisement. Examples of interactions related to an
advertisement include actions before and after viewing an
advertisement, such as: the history of the user's browser that is
being sent an advertisement, the history of the user's browser
having received an advertisement, the user interacting with an
advertisement through mouse-over or click events, and post-click
activity on web pages, such as filling out a form, making a
purchase, or installing an application. The log database 115 is
populated by the interaction receiving engine 165, which reviews
traffic from the user at the client 110 for interactions with
contributors. Data in the log database 115 can in turn be used to
populate other databases in the system.
[0037] The log database 115 can store representations of
interactions that take place in the context of an advertisement, as
well as those that take place in other contexts. As an example, the
log database 115 can store a representation of a user's interaction
with a website, such as for example a review that a user A has
submitted to a website or a questionnaire that user A has answered.
Information that was recorded in connection with the submitted
review or questionnaire response can then be displayed as part of
an advertisement that is presented to another user B, whether or
not user B has interacted with user A, and whether or not the two
users have a relationship with each other.
[0038] As another example, the log database 115 can store
information that is generated in connection with an application,
such as a "share a mood" application. This information may
correspond to information that might also be collected via a user's
interaction with an advertisement.
[0039] Accordingly, data in the log database 115 can be collected
based on user interaction with advertisements, and/or from other
types of interactions and/or data sources. When collected from
non-advertisement-based sources, the data may or may not be similar
to information collected from advertisement-based sources.
Regardless of the source of data in the log database 115, the data
can be provided to users who have had an interaction with the user
from whom the data was collected. Alternatively, in some
embodiments, the data may be provided to any user, for example via
the web, regardless of whether the recipient of the data has had an
interaction with the user from whom the data was collected. In one
embodiment, the determination as to how the data should be made
available is dependent on the preferences of the user from whom the
data was collected. In other embodiments, the determination can be
made based on any of a number of factors.
[0040] The log analysis engine 120 determines a score for each
user, s(U). In one embodiment, this score is an aggregate of the
user's behavior in response to interactions that have been logged
in the log database 115. For example, the score for a user can
indicate how likely the user is to click on a social advertisement,
wherein a social advertisement is one that portrays either i) a
friend of the user from a social network; or ii) a contributor with
regard to subject matter of the advertisement.
[0041] In one embodiment, the user's score is determined from the
combination of at least two groups of measurements. The first group
includes summary statistics of how a particular user responds to
social advertisements. Specifically, in one embodiment, the first
group of statistics can include, for example: [0042] (i) # of
impressions of social advertisements shown to user, across all
friends, over a pre-determined time period of N days; [0043] (ii) #
of "interactions" generated by social advertisements for
impressions of (i); [0044] (iii) # of clicks to an advertiser
landing page for impressions of (i); [0045] (iv) # of actions after
the landing page for impressions of (i); [0046] (v) interaction
rate computed from (i) and (ii); [0047] (vi) clickthrough rate
computed from (i) and (iii); [0048] (vii) conversion rate computed
from (i) and (iv).
[0049] The second group includes summary statistics of how all
users respond to social advertisements. Specifically, in one
embodiment, the second group of statistics can include, for
example: [0050] (i)' # of impressions of social advertisements
shown to all users, across all friends, over a pre-determined time
period of N days; [0051] (ii)' # of "interactions" generated by
social advertisements for impressions of (i); [0052] (iii)' # of
clicks to an advertiser landing page for impressions of (i); (iv)'
# of actions after the landing page for impressions of (i); [0053]
(v)' interaction rate computed from (i) and (ii); [0054] (vi)'
clickthrough rate computed from (i) and (iii); [0055] (vii)'
conversion rate computed from (i) and (iv).
[0056] In one embodiment, the user's score is a function of either
the ratio of the user's interaction rate, v, to all users'
interactions rate, v'; the user's clickthrough rate, vi, to all
users' clickthrough rate, vi'; or the user's conversion rate, vii,
to all users' conversation rate, vii'. Which of these ratios is
used depends on the method of selling the advertisements. The
interactions rate, clickthrough rate and conversion rate shown here
as components of the determination of a user score are conventional
measurements used to price advertising on the Internet. The
interaction rate is based on the number views of an advertisement.
The clickthrough rate is based on the number clicks on an
advertisement and the conversion rate is based on the number of
purchases or other desired action the user undertakes after
clicking on an advertisement.
[0057] In various embodiments, for advertisements that are sold per
impression or per interaction, the user score is based on the
interactions, v, for advertisements sold per click, the user score
is based on the clickthrough rate, vi, and for advertisements sold
per action, the user score is based on the conversion rate, vii.
The function applied to the ratio can be, for example, the identity
function or a sigmoid function.
[0058] Scores for users are stored in the user score database 125.
Determination of user scores by the log analysis engine 120 may
occur asynchronously from the choosing and displaying of an
advertisement to a user. User scores can be updated, for example,
at predetermined intervals, such once a day, once a week, or once a
month.
[0059] It is noted that there may be instances in which there is
not enough information known about a particular user for a user
score to be a valid predictor. In such an instance any
probabilistic technique can be employed, such as Gibbs sampling,
which considers the user score to be a random variable.
[0060] The response database 130 stores responses to advertisements
and/or other forms of contributions or input relevant to the
subject matter of advertisements. Such responses and other input
can be received from friends and/or from other individuals
(referred to herein as "contributors"). A friend is any individual
with which the user has had an interaction on the Internet, while a
contributor may be any individual regardless of whether the user
has had an interaction with the individual.
[0061] For example, friends can include individuals for whom the
user has email addresses in an online address book. Online address
books include address books at email applications such as Yahoo!
Mail.TM. and GMail.TM.. Online address books also include address
books stored at websites from which a user sends links to other
users. An example is Kodak Picture Gallery.TM.. Friends can also
include other individuals that the user has designated as a friend
in a social network such as Facebook.TM. and MySpace.TM..
[0062] The response database 130 may assume any number of forms,
such as a relational database, a memory-based key-value pair
storage system, or flat file format for rapid lookup. In one
embodiment, a memory key-value system is loaded with a set of flat
files built from a relational database of interactions.
[0063] The interaction database 140 stores metadata about
interactions between a user and the user's friends. This metadata
can be used, for example, in determining an interaction score that
is used to determine ranks for the user's friends. In one
embodiment, metadata for a given interaction includes such
information as: the social media site at which the interaction
occurred; the application via which the interaction occurred; the
publisher of the application, if applicable; the type of
interaction; what the interaction was; the user(s) involved; date
and time of the interaction; and how many recipients there were of
the interaction. In one embodiment, metadata stored in the
interaction database 140 for a given interaction is stored in a
uniform format so that the entries are comparable across the
various contexts in which interactions occur on the Internet.
[0064] The friend rank analysis engine 145 computes the ranks of a
user's friends. In one embodiment, this analysis comprises
determining an interaction score based on data from the interaction
database 140 and thereby determining a rank for each of the user's
friends, to be stored in the rank database 135. This rank is a
statistical indication of how much more likely a user is to click
on a social advertisement given that it indicates the advertisement
is directed from a specific friend. In one embodiment, this rank is
determined using weighted sums of counts of interaction data using
Formula (I).
r .function. ( U , F ) = i = 1 n .times. w i .times. c i .function.
( U , F ) x .times. i = 1 n .times. w i .times. c i .function. ( U
, x ) ( I ) ##EQU00001##
[0065] wherein: c.sub.i(U,F) is a count of one type of interaction
between a given user, U, and a given friend, F, n=number of
different types of interactions, x is any one of the user's
friends, and w.sub.i is the weight given to each type of
interaction. Friend rank is described in further detail in
co-pending U.S. Utility patent application Ser. No. 12/277,237 for
"Ranking Interactions Between Users on the Internet", filed Nov.
24, 2008, which is incorporated herein by reference.
[0066] Interaction types include various mechanisms by which a user
can interact with his or her friends. Examples including a user
visiting another user's page within a social network or wedding
planning site, visiting the blog of a friend, viewing photos shared
by a friend at a photo sharing site, explicit hyperlinking of one
user to another user's page, explicit actions by one user with
another user enabled by social networks and social applications, or
the like. In many cases, advertising networks may observe these
interactions with an HTTP_REFERER uniform resource locator ("URL")
attribute, as is available when serving advertisements to
users.
[0067] Additional interaction types include gifts exchanged between
the user and the user's friends using a social network's "gifting
applications," messages sent, invitations, interactions between a
user and the user's friends via social advertisements, news feed
clicks and participation by the user in other social media
applications. Examples of interactions within a social network
include updating a map on the user's page to add a recent trip, a
user going into a drink-sending application, choosing a drink,
choosing a friend, adding a message, and sending the friend that
drink. Interactions between users may be synchronous or
asynchronous.
[0068] In one embodiment, each interaction type is given a weight,
w.sub.i. For example, a message and an invitation might have a
weight of 0.1, the sending of a gift using the gift application of
the social network might have a weight of 0.2, and an interaction
via a social advertisement might have a weight of 0.5. Other
weights might be applied to other types of interactions, including
interactions that may take place between users who do not know each
other.
[0069] The resulting friend ranks are stored in the rank database
135. The friend rank computed by the friend rank analysis engine
145 may operate asynchronously from the process of choosing and
displaying an advertisement to a user. The friend rank may be
pre-computed at pre-determined intervals (such as, for example,
once every 24 hours, once a week, or once a month) or computed in
real time from sufficient statistics.
[0070] In some embodiments, the present invention is adapted to
operate in contexts where an individual presented in an
advertisement is some contributor whose opinion and/or actions may
carry greater relevance than would the opinion of an ordinary user,
even to those who do not personally know the contributor. A
contributor can be an individual having particular expertise, or
can be anyone who has provided an opinion, submitted a review, or
performed some other action with respect to the subject matter of
interest. Since the user would not necessarily have had any direct
interactions with such a contributor, a rank can be developed based
on some other mechanism, such as based on an overall assessment of
the quality of the contributor's reviews or the overall value of
his or her credentials. This rank is referred to as a contributor
rank. Friend rank and contributor rank are referred to herein
collectively as "subject individual rank" (or simply "rank"), and
are stored in the rank database 135; friends and contributors are
referred to herein collectively as "subject individuals".
[0071] Accordingly, in one embodiment, rank database 135 can
include friend ranks as well as contributor ranks, where friend
ranks are derived based on direct interactions between the friend
and the user, and contributor ranks are obtained via other means,
such as (for example) an indication of the popularity of the
contributor. These contributor ranks can be obtained from any
source 146; for example, contributor ranks for contributors can be
obtained from an API provided by a social media website that
provides an indication as to how many followers the contributor
has, or some other indication of the relative popularity or
trustworthiness of the individual. Such API's are available for
most social media websites. In one embodiment, data from the log
analysis engine 120 is used by the contributor rank source 146 to
generate contributor ranks.
[0072] Additionally or alternatively, contributor ranks can be
determined based on the relative performance of advertisements
containing the contributor's identity and/or contributed content;
this assessment can be made, for example, using data from the log
analysis engine to create internal contributor rank sources. Such
internal sources may measure, for example, aggregate click-through
rate for advertisements portraying the contributor and/or
contributed content, aggregate ratings of the contributor's
content, number of comments about the contributor's content, and/or
any other methods of evaluating the contributor and/or contributed
content. Performance and favorability statistics can also be
gathered in other contexts, such as when the contributor and/or
contributed content are displayed in environments other than
directly in an advertisement, such as a landing page, widget, email
message, or other content distribution construct.
[0073] In one embodiment, friend ranks may differ from one user to
another, even for the same subject individual; for example, a
subject individual's friend rank may be higher for user A than for
user B, if the subject individual has had more interactions with
user A than to user B. In one embodiment, a contributor rank for a
given subject individual at a given time is applicable to all users
(although it may change over time); for example, a contributor rank
may be based on an overall assessment of the subject individual's
contributed content, based on comments and/or ratings submitted by
the general public.
[0074] Thus, in one embodiment, the system of the present invention
obtains friend ranks for friends (i.e., individuals with whom the
user has had interactions) based on the nature and degree of such
interactions. As described above, for those individuals with whom
the user has not had interactions (i.e., contributors), the system
of the present invention obtains contributor ranks based on some
other measure, which preferably reflects the degree of the
individual's authoritativeness (based on expertise, experience,
and/or other qualifications) with respect to the subject matter of
an advertisement.
[0075] In one embodiment, friend ranks and contributor ranks are
normalized so that they can be meaningfully compared with one
another. Alternatively, if friend ranks are not available for some
subset of candidate advertisements, contributor ranks can be used,
ignoring any friend ranks that may only be available for some of
the candidate advertisements.
[0076] The advertisement database 150 stores advertisements that
can potentially be displayed to users. Advertisements may be
displayed to a user when the user visits a website on the Internet.
Alternatively, the advertisement can be sent to a user
electronically, such as via email, instant message, telephone call,
via a social network, or the like. Additionally or alternatively,
messages can be sent using a social message utility such as
Twitter.TM..
[0077] The ad rank computation and selection engine 155 determines
ranks of advertisements for a particular user; these ranks are
referred to as "AdRanks". In one embodiment, this determination
includes a computation involving the eCPM, user score, and
aggregated subject individual ranks. A subject individual rank may
be a friend rank for a friend of the user. Ranks can also, in one
embodiment, include contributor ranks for individuals whose
authoritativeness (including expertise, experience, and/or other
qualifications) are relevant to the advertisement; for example,
contributor rank can represent an overall assessment of the quality
of an individual's reviews or the overall value of his or her
credentials. In one embodiment, the aggregated rank is an
aggregation including both friend rank(s) and contributor
rank(s).
[0078] For example, ad rank can be computed as:
Ad Rank=eCPM*s(U)*aggregated ranks for subject individuals
where s(U) represents the user score (also referred to as quality
score).
[0079] The following is an example of the application of the
above-described techniques. Rank values are shown for three subject
individuals, who are friends F1, F2, F3 of a user U1, based on the
friends' responses to advertisements A1 and A2.
TABLE-US-00001 User Subject individual Ad Rank U1 F1 A1 1.5 U1 F2
A1 3.2 U1 F1 A2 1.6 U1 F3 A2 0.9
[0080] The above values can be aggregated as follows, to generate
AdRank values for each advertisement:
TABLE-US-00002 User Subject individuals Ad AdRank(A) U1 F1, F2 A1
Bid eCPM(A1) X f(1.5, 3.2) U1 F1, F3 A2 Bid eCPM(A2) X f(1.6,
0.9)
[0081] That is, given friend rank data for specific response
advertisements from friends, the AdRanks for specific
advertisements can be computed from the individual responses using
a combinator, f. This combinator can be the maximum value,
geometric mean, arithmetic mean, or the like. Given such a
combinatory function and subject individual ranks between users,
AdRanks are developed. These AdRanks can then be used in eCPM
auctions to determine which advertisement to show.
[0082] In one embodiment, the advertisement with the highest AdRank
as computed by the above-described process is displayed (or
otherwise output) to the user at the client 110. In another
embodiment, some set of advertisements have AdRank scores exceeding
a predefined threshold are identified, and one of the identified
advertisements is selected for display (for example, based on a
predefined rotation, random selection, ranking within the set of
identified advertisements, or the like). Interactions that result
from the user being displayed in an advertisement are logged by the
interaction receiving engine 165.
[0083] In some embodiments, multiple advertisements may be
displayed. Accordingly, some advertisements may be displayed more
prominently than others, based (at least in part) on the relative
AdRanks of the advertisements.
[0084] As described above, in one embodiment, the system of the
present invention is able to compare advertisements portraying
friends (individuals with whom the user has had an interaction)
with advertisements portraying contributors (individuals with whom
the user has not necessarily had an interaction), and to generate
comparative ranks for each. The rank for a contributor can be
determined based on the degree to which the contributor is
considered authoritative with respect to the particular subject
matter of the advertisement.
[0085] Extending the example above, suppose subject individual Cl
is a contributor, with a high degree of authoritativeness relevant
to the subject matter of advertisement A1. Then, ranks might be
determined as follows:
TABLE-US-00003 User Subject individual Ad Rank U1 F1 A1 1.5 U1 F2
A1 3.2 U1 F1 A2 1.6 U1 F3 A2 0.9 U1 C1 A1 5.0 U1 C1 A2 0.0
[0086] Note that in this example, the authoritativeness of
individual Cl is considered highly relevant for advertisement A1
but not relevant for advertisement A2. For example, A2 may be a
subjective advertisement such as a "mood ad", wherein the
advertisement portrays the mood of the friend; in such a case the
mood of individual Cl would not be relevant to user U1, since user
U1 does not know individual Cl. Accordingly, the rank of Cl with
respect to advertisement A1 is assigned the relatively high value
of 5.0, while the rank of Cl with respect to advertisement A1 is
assigned a value of zero.
[0087] The above values can be aggregated as follows, to generate
AdRank values for each advertisement:
TABLE-US-00004 User Subject individuals Ad AdRank(A) U1 F1, F2, C1
A1 Bid eCPM(A1) X f(1.5, 3.2, 5.0) U1 F1, F3, C1 A2 Bid eCPM(A2) X
f(1.6, 0.9, 0.0)
[0088] In one embodiment, some set of candidate advertisements is
available, and the system of the present invention selects an
advertisement from the set of candidates. For example, in response
to a client's 110 request for an advertisement, five candidate
advertisements might be identified (based, for example, or certain
demographic and/or geographic characteristics of the user
associated with the client 110). Some of these candidate
advertisements may be designated as "social advertisements" that
only include friends, meaning that they will only be shown if a
friend of the user has previously interacted with an equivalent
advertisement. Thus, if no friends have interacted with a candidate
(as determined based on data from the response database 130), that
candidate is eliminated as a potential advertisement to be shown.
Of those advertisements that remain, the system of the present
invention determines which advertisement to show, and which friend
to portray in the advertisement, based on the ad ranking mechanism
described above. A representation of the selected friend is then
inserted in the advertisement, and the advertisement is transmitted
to the client 110 for display to the user. Alternatively, some
candidate advertisements may be designated as "social
advertisements" that may include all types of subject individuals,
whether they are friends or not. In this case, the candidate
advertisement may be considered for display to any user, ignoring
other targeting and ad parameters, as long as there is at least one
individual who has contributed content pertaining to the candidate
advertisement (as determined based on data from the response
database 130).
Process Flow
[0089] Referring now also to FIG. 4, there is shown a flow diagram
depicting a method for displaying an advertisement to a target user
according to one embodiment. A target user visits 401 a website and
the browser at the client 110 requests 402 an advertisement. The ad
rank computation and selection engine 155 receives the request and
in turn, and obtains 403 the target user's overall score s(U) from
the user scores database 125 as well as subject individual ranks,
which may include contributor ranks and/or friend ranks for the
target user's friends from the friend rank database 135. The ad
rank computation and selection engine 155 also obtains 404
advertisements from the advertisement database 150. Using the
mechanism described previously, the ad rank computation and
selection engine 155 selects 405 an advertisement (or
advertisements) for display. If the subject individual (a friend or
contributor) is not already depicted in the advertisement, he or
she can be inserted 409 in the advertisement.
[0090] In one embodiment, insertion 409 of the subject individual
is performed as follows. Each advertisement has at least one
placeholder location in which the representation of the subject
individual can be inserted. The placeholder location can be
designated for a picture, name, animation, or other identifier.
When the advertisement is rendered as HTML to be sent to the client
110, a representation of the subject individual is inserted at the
location of the placeholder. One skilled in the art will recognize
that many other mechanisms for inserting the subject individual's
representation can be used, including for example insertion via
Adobe.TM. Flash.TM. or some other multimedia software application.
Alternatively, advertisements can be pre-rendered in static form,
as a file in JPG, GIF, PNG or other image format, to include the
subject individual along with other advertising content.
[0091] In one embodiment, the picture, name, animation or other
representation of the subject individual is obtained from a
database (not shown) containing such information for all potential
subject individuals. The database can include actual images and
other content, or can include links (pointers), for example in the
form of URLs.
[0092] The selected advertisement is then transmitted 406 to the
target user's browser at the client 110, which displays 407 the
advertisement.
[0093] As discussed above, in one embodiment, the displayed
advertisement may portray any subject individual, including a
friend of the target user, or any other individual with whom the
friend has interacted, for example in the context of a social media
application (which may or may not be the same social media
application in which the advertisement is being presented). In
another embodiment, the subject individual portrayed in an
advertisement may be an individual that the target user has not
necessarily interacted with; the individual in the advertisement
may be a contributor or other individual whose opinion, expertise,
or action may be relevant to the subject matter of the
advertisement. In this manner, effectiveness of the advertisement
is improved, because the target user is more likely to pay
attention to and/or trust the content of the advertisement when the
advertisement includes a portrayal of a friend, contributor, and/or
other trusted individual. The target user's interaction with the
advertisement is logged 408 at the interaction receiving engine
165.
Example User Interfaces and Interactions
[0094] Referring now to FIG. 3A, there is shown a screenshot 300 of
a user interface displaying an advertisement 301 to a first user
according to one embodiment. The advertisement invites the first
user (a subject individual) to respond to the question about how
the first user is feeling today, by selecting among icons 302A-D.
The first user chooses mood icon 302B as a response and that
response is transmitted to the system and stored in the log
database 115.
[0095] Referring now to FIG. 3B, there is shown a screenshot 310 of
a user interface, according to one embodiment, displaying the
interface after the first user has interacted with the
advertisement 301. The advertisement 301 now reflects the first
user's choice of mood and invites the first user to click through
the advertisement (by clicking on button 311) to access the
advertiser's website. The first user's interaction with the
advertisement 301, such as clicking on button 311, is stored in the
log database 115.
[0096] Referring now to FIG. 3C, there is shown a screenshot 320 of
a user interface, according to one embodiment, displaying the
advertiser's website 321 as it appears after the first user has
clicked on button 311 in the advertisement 301 of FIG. 3B. The
first user's interactions with the advertiser's website 321,
including for example, purchases, are stored in the log database
115.
[0097] As described above, the first user's interactions with the
advertisement 301 can be used in the generation and presentation of
an advertisement for a second user, so that the first user becomes
a subject individual portrayed in the advertisement shown to the
second user. Referring now to FIG. 3D, there is shown a screenshot
330 of a user interface, according to one embodiment, displaying to
a second user an advertisement 331 including a portrayal, or
representation 332, of the first user. In the example of FIG. 3D,
representation 322 is a photograph; however, one skilled in the art
will recognize that the representation 332 can be a name, user ID,
sketch, icon, handle, or any other indicator of the first user's
identity, whether a fictional identity or an actual identity. The
representation 332 can be visual, animated, text-based, numeric,
icon-based, or of any other type.
[0098] In one embodiment, a screenshot 330 such as shown in FIG. 3D
can be generated according to the process flow described above in
connection with FIGS. 1 and 4. Thus, prior to displaying the
advertisement 331 in FIG. D, the system of the present invention
determines an advertisement to display and selects a subject
individual (friend or contributor) to portray in the advertisement.
In this example, the subject individual shown in the advertisement
331 is the first user (i.e., the user who interacted with the
advertisement 301 shown in FIG. 3A), as this first user has been
identified as a friend of the second user.
[0099] In this example, the advertisement 331 shown in FIG. 3D
informs the second user how the first user is feeling, by including
a representation 332 of the first user along with an icon 333
corresponding to the mood icon 102 selected by the first user in
FIG. 3A. The second user is then invited to select an icon 302A-D
that illustrates the second user's mood. When the second user does
so, by clicking on icon 302B, the response is stored in the log
database 115.
[0100] Referring now to FIG. 3E, there is shown a screenshot 340 of
a user interface, according to one embodiment, displaying the
interface after the second user has interacted with the
advertisement 331. The advertisement 331 now reflects the first
user's choice of mood and invites the second user to click through
the advertisement (by clicking on button 311) to access the
advertiser's website. The second user's interaction with the
advertisement 331, such as clicking on button 311, is stored in the
log database 115.
[0101] Referring again to FIG. 3C, there is shown a screenshot 320
of a user interface, according to one embodiment, displaying the
advertiser's website 321 as it appears after the second user has
clicked on button 311 in the advertisement 331 of FIG. 3E. The
second user's interactions with the advertiser's website 321,
including for example, purchases, are stored in the log database
115.
[0102] In the above description, for illustrative purposes,
advertisements are depicted as visual components of web pages.
However, one skilled in the art will recognize that advertisements
selected and presented in connection with the present invention can
take any form, including visual, auditory, text-based, or any
combination thereof. For example, and without limitation,
advertisements can be animations, audio messages, text messages,
email messages, multi-media messages, or the like. Advertisements
may or may not conform to accepted standards such as those
promulgated by the Internet Architecture Board (IAB), and may be
static or dynamic in size.
Broadcasting User Interactions
[0103] In one embodiment, the interactions of a user (i.e., a
subject individual) with an advertisement are made publicly
available, for example via an advertisement that is broadcast via
the web or by any other communications medium. Thus, an
advertisement can be broadcast that includes a representation (such
as a photograph, name, or other identifier) of a subject individual
who has interacted with the same advertisement, or who has
interacted with another advertisement. In another embodiment, the
broadcast advertisement can include a representation of a user
(i.e., a subject individual) who has otherwise contributed an
opinion or response relevant to the subject matter of the
advertisement, such as by submitting a review or answering a
questionnaire. The advertisement can be broadcast to the general
public, or to a selected group of individuals based on some
characteristic (such as demographics, geography, subject matter of
interest, website visited, and the like). The determination of
which users should receive the advertisement can be made based on
any parameters or characteristics, including for example a computed
affinity or similarity between the subject individual and the user
being presented the advertisement. Such an affinity or similarity
can be used as a basis for presenting the advertisement to a user
even if that user does not necessarily know the subject
individual.
[0104] An advertisement shown in such an embodiment would resemble
the advertisement 311 depicted in FIG. 3D, where the representation
332 portrays a subject individual who has interacted with the same
advertisement, or who has interacted with another advertisement.
Here, however, the advertisement 311 is broadcast to the general
public or to a selected group of individuals based on some
characteristic, regardless of whether or not the target individuals
personally know (or have interacted with) the subject individual.
In this example, previous to broadcasting this advertisement 311,
the subject individual portrayed in the representation 332 has
interacted with this or another advertisement to indicate that he
is in a certain mood, designated by the icon 302B.
[0105] In the above description, the invention has been described
in the context of an embodiment wherein responses of friends and
other contributors are considered, and wherein friends and/or other
contributors can be portrayed in advertisements to a target user.
One skilled in the art will recognize that other embodiments can be
implemented, including for example an embodiment where only the
responses of friends are considered, and only friends of the target
user are eligible to be presented in advertisements.
[0106] Numerous specific details have been set forth herein to
provide a thorough understanding of the embodiments. It will be
understood by those skilled in the art, however, that the
embodiments may be practiced without these specific details. In
other instances, well-known operations, components and circuits
have not been described in detail so as not to obscure the
embodiments. It can be appreciated that the specific structural and
functional details disclosed herein may be representative and do
not necessarily limit the scope of the embodiments.
[0107] In addition, some portions of the detailed description, such
as the processes described in reference to FIG. 1, are presented in
terms of algorithms and symbolic representations of operations on
data bits within a computer memory, such as memory 206. These
algorithmic descriptions and representations are the means used by
those skilled in the data processing arts to most effectively
convey the substance of their work to others skilled in the art. An
algorithm is here, and generally, conceived to be a self-consistent
sequence of processing steps (instructions) that, when executed by
a processer such as processor 202, lead to a desired result. The
steps are those requiring physical manipulations of physical
quantities. Usually, though not necessarily, these quantities take
the form of electrical, magnetic or optical signals capable of
being stored, transferred, combined, compared and otherwise
manipulated. It is convenient at times, principally for reasons of
common usage, to refer to these signals as bits, values, elements,
symbols, characters, terms, numbers, or the like. Furthermore, it
is also convenient at times, to refer to certain arrangements of
steps requiring physical manipulations of physical quantities as
modules or code devices, without loss of generality.
[0108] Further, the features and advantages described in the
specification provide a beneficial use to those making use of a
system and a method as described in embodiments herein. For
example, a user is provided mechanisms, e.g., by receiving and/or
transmitting control signals, to control access to particular
information as described herein. Further, these benefits accrue
regardless of whether all or portions of components, e.g., server
systems, to support their functionality are located locally or
remotely relative to the user.
[0109] Some embodiments may be described using the expression
"coupled" and "connected" along with their derivatives. It should
be understood that these terms are not intended as synonyms for
each other. For example, some embodiments may be described using
the term "connected" to indicate that two or more elements are in
direct physical or electrical contact with each other. In another
example, some embodiments may be described using the term "coupled"
to indicate that two or more elements are in direct physical or
electrical contact. The term "coupled," however, may also mean that
two or more elements are not in direct contact with each other, but
yet still co-operate or interact with each other. The embodiments
are not limited in this context.
[0110] Unless specifically stated otherwise, it may be appreciated
that terms such as "processing," "computing," "calculating,"
"determining," or the like, refer to the action and/or processes of
a computer or computing system, or similar electronic computing
device, that manipulates and/or transforms data represented as
physical quantities (e.g., electronic) within the computing
system's registers and/or memories into other data similarly
represented as physical quantities within the computing system's
memories, registers or other such information storage, transmission
or display devices. The embodiments are not limited in this
context.
[0111] As used herein any reference to "one embodiment" or "an
embodiment" means that a particular element, feature, structure, or
characteristic described in connection with the embodiment is
included in at least one embodiment. The appearances of the phrase
"in one embodiment" in various places in the specification are not
necessarily all referring to the same embodiment.
[0112] Upon reading this disclosure, those of skill in the art will
appreciate still additional alternative systems and methods for
targeted advertising using data captured by social networking
applications in accordance with the disclosed principles herein.
Thus, while particular embodiments and applications have been
illustrated and described, it is to be understood that the
embodiments are not limited to the precise construction and
components disclosed herein and that various modifications, changes
and variations which will be apparent to those skilled in the art
may be made in the arrangement, operation and details of the method
and apparatus disclosed herein without departing from the spirit
and scope of the disclosure and appended additional claimable
subject matter.
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