U.S. patent application number 11/541436 was filed with the patent office on 2007-04-05 for contributor reputation-based message boards and forums.
Invention is credited to Craig A. Kaplan.
Application Number | 20070078675 11/541436 |
Document ID | / |
Family ID | 41194439 |
Filed Date | 2007-04-05 |
United States Patent
Application |
20070078675 |
Kind Code |
A1 |
Kaplan; Craig A. |
April 5, 2007 |
Contributor reputation-based message boards and forums
Abstract
System and method for operating reputation-based communication
or content service. Method includes obtaining metric related to
first user contributor reputation; identifying communication or
content having association with first user contributor; and
processing communication or content to generate processed
communication or content based on the obtained objective
contributor reputation. Service is broadly defined and may be
selected from bulletin board, message board, chat room, forum,
information provision service, content delivery service, email
service, information provision service, search engine service,
content delivery service, communication or content screening
service, communication or content screening service, or other.
System for providing reputation processed based on-line
communication or content. Communication or content provided or
generated by the inventive system or method. Business method for
operating a communications or content provision service. Computer
program and computer program product stored either on a tangible
media or in an electronically accessible and readable form to
implement method.
Inventors: |
Kaplan; Craig A.; (Aptos,
CA) |
Correspondence
Address: |
PERKINS COIE LLP
P.O. BOX 2168
MENLO PARK
CA
94026
US
|
Family ID: |
41194439 |
Appl. No.: |
11/541436 |
Filed: |
September 29, 2006 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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60722101 |
Sep 30, 2005 |
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Current U.S.
Class: |
705/26.1 ;
705/319 |
Current CPC
Class: |
G06Q 30/0601 20130101;
G06Q 50/01 20130101; G06Q 10/10 20130101 |
Class at
Publication: |
705/001 |
International
Class: |
G06Q 99/00 20060101
G06Q099/00 |
Claims
1. A method for operating a reputation-based communication or
content service, the method comprising: obtaining at least one
metric related to a first user contributor reputation; identifying
a communication or content having an association with the first
user contributor; and processing the communication or content to
generate a processed communication or content based on the obtained
objective contributor reputation.
2. A method as in claim 1, further including processing the
communication or content along with other different communications
or content from other different contributors based at least in part
on the objective contributor reputation of one or of a plurality of
contributors.
3. A method as in claim 1, wherein the service is selected from the
set of services consisting of an online bulletin board, an online
message board, a chat room, a forum, a information provision
service, a content delivery service, an email service, an
information provision service, a search engine service, a content
delivery service, a communication or content screening service, a
communication or content screening service, and any combination of
these.
4. A method as in claim 1, wherein the obtaining at least one
metric related to a first user contributor reputation comprises the
step of collecting the at least one metric related to a first user
contributor reputation.
5. A method as in claim 4, wherein the collecting the at least one
metric related to a first user contributor reputation is performed
automatically by the method without a separate conscious input by
the user contributor.
6. A method as in claim 1, wherein the obtaining at least one
metric related to a first user contributor reputation comprises
obtaining the at least one metric related to a first user
contributor reputation from an external source.
7. A method as in claim 1, wherein the identifying of the
communication or content comprises: at least one of: (i) receiving
a first communication or content from the first user contributor;
and (ii) identifying a contribution or content attributed at least
in part to the first user contributor.
8. A method as in claim 1, wherein the identifying of a
communication or content having an association with the first user
contributor comprises
9. A method as in claim 1, further comprising sending a second
communication to a user that includes the generated processed
communication or content or portion thereof.
10. A method as in claim 1, further comprising: obtaining at least
one metric related to a plurality of different user contributor
reputations; identifying a communication or content having an
association with each of the plurality of user contributors; and
processing the plurality of communications or contents to generate
a processed communication or content based on the obtained
objective contributor reputation for the plurality of different
user contributors.
11. A method as in claim 1, wherein the processing based on
objective reputation comprises a processing selected from the set
consisting of filtering, sorting, ordering, screening, compiling,
grouping, deleting, flagging, hiding, highlighting, promoting, and
any combination of these based on objective reputation of a
contributor or a plurality of contributors.
12. A method as in claim 11, wherein the processing may be
different for different contributors or for different groups of
contributors.
13. A method as in claim 1, wherein the processing based on
objective reputation includes a processing selected from the set
consisting of: filtering to include some items and not others based
on objective reputation of the contributor or group of
contributors, filtering based on objective reputation of the
contributor or group of contributors, filtering to exclude some
items and not others based on objective reputation of the
contributor or group of contributors, compiling a set of relevant
content based on objective reputation of the contributor or group
of contributors, ordering based on objective reputation of the
contributor or group of contributors, ordering from low to high
based on objective reputation of the contributor or group of
contributors, ordering from high to low based on objective
reputation of the contributor or group of contributors, selecting
or not selecting based on objective reputation of the contributor
or group of contributors, processing based on objective reputation
of the contributor or group of contributors, generating derivative
objective reputation data based on objective reputation of the
contributor or group of contributors, and any combination of
these.
14. A method as in claim 1, wherein the service is a communication
forum selected from the set of forums consisting of a network site,
an Intranet site, an Internet site, a world wide web site, an
electronic mail or email, an interactive electronic bulletin board,
an interactive electronic message board, an online information
exchange, a set of email or comment threads, an online interactive
stock prediction forum, an online forum, and any combination of
these.
15. A method as in claim 1, wherein the reputation metric comprises
a factually based objective contributor reputation established in
the same field of endeavor as the contribution being
communicated.
16. A method as in claim 1, wherein the objective contributor
reputation comprises a historical accuracy-based reputation.
17. A method as in claim 16, wherein the historical accuracy-based
reputation is for a contribution in the same field as the
reputation was established.
18. A method as in claim 1, wherein the step of collecting
objective metrics, comprises collective objective metrics
automatically without compelling a user take separate actions to
provide objective metrics of information from which objective
metrics are derived.
19. A method as in claim 1, wherein the method further comprising
matching these reputation metrics closely to the topic of the
particular communication forum.
20. A method as in claim 1, further comprising filtering
contributor postings with a predetermined objective accuracy and
without a conscious human input contribution relative to a
filtering metric.
21. A method as in claim 1, wherein the method further includes
automatically tracking the accuracy of contributors who provide an
online prediction or forecast of an element and generating a
prediction accuracy result by comparing the prediction of the
element with the actual value of the element at the predicted time
and date, and automatically generating a prediction accuracy for
the contributor based on that comparison.
22. A method as in claim 21, wherein the element is an online stock
price prediction.
23. A method as in claim 1, wherein reputation metrics are be
subjected to aging or other refinement so that recent objective
history is given a greater objective weight or older performance
may be discounted or not considered at all.
24. A method as in claim 1, wherein collected or otherwise directly
or indirectly available reputation metrics are processed to make
them more useful.
25. A method as in claim 1, wherein the processing to make them
more useful comprises applying a statistical processing to a least
one objective reputation metric.
26. A method as in claim 1, wherein the applied statistical
processing is selected from the set of statistical processing
comprising: computing a weighted average over time, normalizing the
reputation or plurality of reputations so that one contributor's
reputation can be compared with another contributor's reputation
according to some defined comparison criteria.
27. A method as in claim 1, wherein the defined comparison criteria
comprises an objective comparison criteria.
28. A method as in claim 1, wherein the objective reputations
comprise raw reputations, processed reputations, or any combination
of raw reputations and processed reputations.
29. A method as in claim 1, wherein the method further includes
filtering or automatically selecting contributions to be seen or
presented to a user based on an objective metric or combination of
a plurality of metrics.
30. A system for providing a reputation processed based on-line
communication or content, the system comprising: a contributor
reputation metric collection component; a communication or content
medium identification component; and a communication or content
reputation processing component.
31. A system as in claim 30, wherein the collection component
comprises a automatic collection component for collecting the
reputation metric related to a contributor reputation automatically
without a separate conscious input by a user contributor.
32. A system as in claim 31, wherein the at least one reputation
metric is obtained from an external source.
33. A system as in claim 30, wherein the contributor reputation
metric identification component includes means for identifying of
the communication or content selected from the set consisting of:
(i) receiving a first communication or content from the first user
contributor; and (ii) identifying a contribution or content
attributed at least in part to the first user contributor.
34. A system as in claim 33, wherein the communication or content
reputation processing component comprises a processing unit adapted
for processing selected from the set of processing schemes
consisting of filtering, sorting, ordering, screening, compiling,
grouping, deleting, flagging, hiding, highlighting, promoting, and
any combination of these based on objective reputation of a
contributor or a plurality of contributors.
35. A system as in claim 34, wherein the processing may be
different for different contributors or for different groups of
contributors.
36. A system as in claim 35, wherein the communication or content
reputation processing component comprises a processing unit adapted
for processing selected from the set of processing schemes
consisting of filtering, sorting, ordering, screening, compiling,
grouping, deleting, flagging, hiding, highlighting, promoting, and
any combination of these based on objective reputation of a
contributor or a plurality of contributors.
37. A system as in claim 30, wherein the communication or content
medium component is selected from the set consisting of a network
site, an Intranet site, an Internet site, a world wide web site, an
electronic mail or email, an interactive electronic bulletin board,
an interactive electronic message board, an online information
exchange, a set of email or comment threads, an online interactive
stock prediction forum, an online forum, and any combination of
these.
38. A system as in claim 30, wherein the communication or content
medium component further includes (a) means and for entering
information, and (b) means for displaying information.
39. A system as in claim 30, wherein the communication or content
filtering component provides means for sorting, limiting,
compiling, or otherwise modifying {other wise modifying is good,
otherwise it sounds like only limiting and filtering and we are
missing other forms of processing like compiling} the display of
information that has been entered based on metrics that have been
collected.
40. A communication or content processed according to the method of
claim 1.
41. A computer program product stored in an electronically
accessible media for altering the operation of a computer system or
computer network, the computer program product including executable
computer program instructions for causing the computer to generate
a processed reputation-based communication or content and
comprising instructions for: obtaining at least one metric related
to a first user contributor reputation; identifying a communication
or content having an association with the first user contributor;
and processing the communication or content to generate a processed
communication or content based on the obtained objective
contributor reputation.
42. A business method for operating a reputation-based
communication or content provision service, the business method
comprising: obtaining at least one metric related to a first user
contributor reputation; identifying a communication or content
having an association with the first user contributor; processing
the communication or content to generate a processed communication
or content based on the obtained objective contributor reputation;
providing the processed communication or content to a subscriber;
and receiving a renumeration from the subscriber in exchange for
the provided processed communication or content.
43. A business method as in claim 42, wherein the renumeration is a
financial renumeration, a service renumeration, a commission
renumeration, a referral renumeration, or any combination of these.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This patent application claims the benefit of priority to
U.S. Provisional Patent Application Ser. No. 60/722,101 filed 30
Sep. 2005 and entitled Reputation-Based Boards, which application
is hereby incorporated by reference.
[0002] This application also claims priority to U.S. application
Ser. No. 11/______, filed 22 Sep. 2006 entitled Graphical
Forecasting Interface, by Craig A. Kaplan and Calen Lopata,
Attorney Docket No. 61117.8004. US01 and PCT/US06/______, filed on
22 Sep. 2006, entitled Graphical Forecasting Interface by Craig A.
Kaplan and Calen Lopata, Attorney Docket No. 61117-8004 W001, which
applications are hereby incorporated by reference.
FIELD OF THE INVENTION
[0003] This invention pertains generally to Internet, web, and
network-based message boards and forums, chat rooms, email, and
other forms of asynchronous and synchronous communication and more
particularly to such message boards and forums, chat rooms, email
and the like for which a contributor or poster reputation is
automatically evaluated on some objective criteria and used to
rank, rate, or filter contributions, postings, or other content
contributed by or attributed to the contributor or poster.
BACKGROUND
[0004] Currently, many message boards and forums exist online. For
example, Raging Bull is a popular message board where investors can
post their thoughts about the prospects of various stocks.
SlashDot.org is a forum where members can post their thoughts about
technology issues, and rate the posts of others. Particularly
useful is SlashDot's capability of filtering, or ordering, posts
based on how other readers subjectively scored or liked the posts.
Unfortunately, the method of collaborative filtering employed by
Slashdot, and by many other sites, relies on subjective judgment,
after the fact. That is, readers spend time reading a post and then
some of them offer subjective judgments as to quality or how much
they liked or disliked the post.
[0005] Although somewhat useful, there are inherent inefficiencies
and deficiencies in these conventional methods. First, many people
will read a posting but not everyone rates the posting. This means
that a few people with strong opinions (and possibly a single or a
few people with multiple user identities or IDs) can bias the
system by rating early and often. Second, many people still have to
search and/or wade through poor quality information that has
limited or no quality ratings while waiting for the information to
be scored by others. Third, the "quality" of a post is very
subjective. In general, what one person may think of as being
useful, another person may classify or rate as useless or junk.
Most sites do not have rigorous criteria for making objective
quality ratings or even subjective quality ratings. Even if these
rigorous criteria were added, such criteria would be time consuming
to learn and apply and would likely reduce user participation. Any
enforcement of the criteria would also be difficult or impossible
to implement in practical terms. Thus, the current state-of-the-art
is a relatively crude filtering capability that is subjective at
best, that can be applied only after a post or submission has been
written, and that works (if at all) by shifting the burden of
quality control to the users of a web site or other interactive or
on-line forum.
[0006] No known on-line sites, message boards, plural user
contributed or other forums or the like are known that use or have
a capability of filtering posts or contributions, in advance, based
on the reputation of the poster or contributor especially of sites,
message boards, and/or forums where there are a plurality of
posters or contributors other than for example a site, message
board, or forum administrator or originator.
[0007] A major difficulty in constructing such a system to date has
been the challenge of obtaining reliable and objective information
on the quality of posters or contributors. As mentioned above, a
site like SlashDot necessarily relies on the subjective judgment of
their readers to assign scores. Other sites that have quality
rating systems (e.g., the on-line auction site Ebay) also typically
rely on subjective user ratings. When raters know that they too
will be rated (as for example on Ebay) the "reputations" become
even less reliable since people are reluctant to give poor ratings
for fear they will receive negative ratings in retaliation.
Furthermore, since many posters are one-time posters or infrequent
posters, it is often impossible to reliably predict even the
subjective quality of posts in advance. There simply aren't enough
data points to create a reliable trend in most cases.
[0008] Briefly then, conventional systems and methods in use today
in the Internet and on-line posting domain is the filtering of
posts based on subjective quality ratings of the posts, and no
apparent attempt to filter posts based on an objective quality
metric of the poster. In the user reputation domain, we see
Ebay-like subjective commentaries or evaluations (not objective
reputations) that are usually inflated and not very useful (and not
reliable in any event) until many data points (e.g., many
transactions) have been established.
SUMMARY OF THE INVENTION
[0009] In one aspect, the invention provides a method for operating
a reputation-based communication or content service including the
steps of obtaining at least one metric related to a first user
contributor reputation; identifying a communication or content
having an association with the first user contributor; and
processing the communication or content to generate a processed
communication or content based on the obtained objective
contributor reputation.
[0010] In another aspect the method is provided in a service is
selected from the set of services consisting of an online bulletin
board, an online message board, a chat room, a forum, a information
provision service, a content delivery service, an email service, an
information provision service, a search engine service, a content
delivery service, a communication or content screening service, a
communication or content screening service, and any combination of
these.
[0011] In another aspect, the invention provides a system for
providing a reputation processed based on-line communication or
content, the system comprising: a contributor reputation metric
collection component; a communication or content medium
identification component; and a communication or content reputation
processing component.
[0012] In one aspect, the invention provides a communication or
content provided or generated by the inventive system or
method.
[0013] In another aspect, the invention provides a business method
and business model for operating a communications or content
provision service.
[0014] In another aspect the invention provides a computer program
and computer program product stored either on a tangible media or
in an electronically accessible and readable form.
BRIEF DESCRIPTION OF THE DRAWINGS
[0015] FIG. 1 is an illustration showing an exemplary embodiment of
a system for providing and using the inventive reputation-based
message board, web site, forum, chat room, other communications or
content based or related site or service, or the like.
[0016] FIG. 2 is an illustration showing an embodiment of a simple
input box for a message board or comment entry from a pre-release
mock-up of a predictwallstreet.com web site.
[0017] FIG. 3 is an illustration showing an embodiment of a simple
reputation-based bulletin board (RBB) as if might appear if posts
were sorted by reputation for accuracy.
[0018] FIG. 4 is an illustration showing an Illustrative dropdown
or pull-down filtering control.
[0019] FIG. 5 is an illustration showing a flow-chart diagram of an
embodiment of the inventive method.
DETAILED DESCRIPTION OF EMBODIMENTS OF THE INVENTION
[0020] The current invention is provides system, device, method,
computer program, and business method for filtering posts based on
objective quality metrics (e.g., the objective performance track
record or reputation) of the poster. This performance track record
or reputation may be based on historical past performance. The
invention is referred to as Reputation-Based Boards (RBB) at least
in part because it is the reputation (e.g. objective performance
track record) of the poster that drives filtering (typically) of
posts on message boards. The objective performance track record may
for example be an objective performance accuracy track record or
history.
[0021] RBB is not limited only to message boards, web sites, or
forums and the inventive RBB system and methodology which refer to
each of these and others can add significant value to any type of
bulletin board, message board, or other form of online information
exchange where the information source or component of the
information source can be identified or "tagged" with a poster
reputation. The more objective and quantifiable the reputation can
be, the better. By way of example but not of limitation, a licensed
medical surgeon posting on an online forum about a surgery may have
an online reputation that reflects the number (and/or percentage)
of successful surgeries completed or years of surgical practice or
some other factual objective measure; and, a stock forecaster might
have an online reputation that reflects the percentage of correct
stock predictions or some other objective measure of the posters
stock forecasting prediction performance.
[0022] By collecting objective metrics automatically and matching
these reputation metrics closely to the topic of the message board,
it is possible to filter posts with much greater objective
accuracy, and with much less human effort, than existing
conventional collaborative filtering schemes (such as for example
Slashdot) or reputation-rating schemes (such as for example Ebay).
By way of example but not limitation, it may be understood that the
www.PredictWallStreet.com website (developed and operated by the
inventor of the present invention) automatically tracks the
accuracy of individuals who predict stock prices online. Accuracy
is tracked for every prediction allowing the site to assign very
specific, 100% objective, reputations to predictors.
[0023] In one exemplary embodiment of determining, associating, or
assigning reputations, the reputation associated with a particular
poster or contributor may be very closely tied to the posting or
contribution made, even within a particular field. Consider use
Joe, an online stock forecaster, who may have correctly predicted
the movement of IBM stock 80% of the time, but only correctly
predicted the movement of Wal-Mart stock 50% of the time. This past
objective performance seems to suggest that Joe has more insight or
understanding into IBM stock (or perhaps the stock market segment
in which IBM stock belongs) than to Wal-Mart (or perhaps it's
market segment). Therefore, when Joe posts messages about IBM (on
the IBM stock message board) he would have a strong reputation due
to his relatively accurate track record of correct predictions. On
the Wal-Mart stock message board, his reputation would be
relatively poor. Reputations may be subjected to aging or other
refinement so that recent objective history is given a greater
objective weight, or stated differently, older performance may be
discounted or not considered at all. In addition reputations may be
transformed or processed by any one or combination of a variety of
different types of deterministic or statistically based algorithms
and statistical formulas or computations, if such transformations
or processing proves to yield more useful reputations or reputation
based results.
[0024] Note that nobody needs to read and score Joe's posts or
contributions (in this case stock forecasts) in an attempt to
subjectively determine their quality. Instead, the posts may be
automatically filtered based on Joe's objective reputation--a
reputation that can be specific to each message board, on-line
forum, or other source. For example, another user Steve may go to
the message board and request to see only posts by people who have
had an 80% or better track record. On the IBM board, Steve will see
Joe's posts since Joe's contribution meets or exceeds the
performance criteria of 80%. On the Wal-Mart board, Joe's posts
won't appear because his track record (50%) is below the threshold
set by Steve. Of course, rather than setting a threshold, Steve
might just ask to see the posts ranked by the most accurate
predictions first, or filtered in other ways. Criteria need not be
numeric either and may be set into performance categories such as
very reliable, usually reliable, questionable, erratic, or any
other category that may be established to represent the objective
past performance of the poster or contributor. The point is that
Steve can make a much more informed decision about what to do with
the information in Joe's post because Steve knows that Joe's
reputation is based on objective performance criteria. Further, all
readers are saved the chore of rating others. The system collects
the reputation metrics automatically.
[0025] Many variations of the RBB invention are possible and it can
be applied to a wide range of domains. Two main sources of added
value (among others) are: (1) that objective metrics are collected
automatically, and (2) the ability to filter or automatically
select posts to see based on these metrics.
[0026] One of the advantages of a RBB is that it establishes a
reputation, even if the poster has made no previous posts. With
PredictWallStreet.com, for example, a predictor who has done
consistently well over many predictions will have a good reputation
starting with his or her very first post. When RBB is combined with
means of acquiring many objective performance metrics points easily
and quickly (as explained in greater detail in the paragraphs to
follow), it becomes especially powerful and valuable.
[0027] Attention is now directed to a particular exemplary
embodiment of the invention that includes three primary components:
(1) a metric collection component, (2) a communication medium
component or system such as a message board component or system
which in a non-limiting embodiment includes (a) means and method
for entering information, and (b) means and method for displaying
information; and (3) a filtering mechanism and method which allows
the message board to sort or otherwise modify the display of
information that has been entered, based on the metrics (such as
poster reputation) that have been collected. Other embodiments of
the invention may separately include the individual components with
the others being optional.
[0028] We first describe a system on which embodiments of the
invention may be practiced. It will be appreciated that as
embodiments of the invention may be implemented on virtually any
computer system having a first node or machine for hosting the web
site, message board, forum or other posting entity, and that the
poster of contributor may be on any other (or even the same server
or other host machine) computer machine or information appliance,
the invention is applicable to almost an unlimited variety of
machine types and/or architectures and the exemplary embodiment is
merely illustrative and not limiting.
[0029] FIG. 1 shows an exemplary embodiment of a system 51,
incorporating a server 52 that may serve to interact with one or
more users 54 over an interactive electronic medium such as
computers 56 or other information appliances coupled to the server
52 over a network 60 such as the Internet. Network, server, and
computer and communications links that are conventional in nature
and not shown in the figure to avoid obscuring aspects of the
invention.
[0030] The server 52 may include one or more processors 72 and
processor coupled or associated memory 73 for any processing tasks
that may be required. Such processing tasks may include controlling
communications over the network to and from users, accessing one or
more integrated or separate storage devices 74 such as for example
hard disk drive persistent mass storage devices that may store
programs, data, and other system, contributor, reputations, and/or
other data and/or information described herein. Processing may also
include activities of activities in support of processing user
contributed information or information relative to rankings,
ratings, reputations of the like as described herein elsewhere.
[0031] A user may access the server from a client side computer or
information appliance (machine) 77 over the network communication
link or line 78. The user may be provided with a computer program
code or applet to display and interface with the server. Local
storage may be provided on the local user computer or information
appliance for storing data, tokens, cookies, or other identifiers
or information.
[0032] Although a single server is illustrated, the functions and
operations performed by the server may be distributed over a
plurality of servers either for the purpose of scalability,
redundancy, performance or for other reasons.
[0033] Attention is now directed to a description of one particular
embodiment of the inventive system and method, which includes three
main components: (1) a metric collection component; (2) a site,
message board, and/or forum component which advantageously may
include means and method for enter information and optionally but
advantageously means and method for displaying information; and,
(3) a rating, ranking, and/or filtering component which
advantageously provides a mechanism which allows the site, message
board, forum or the like to sort or otherwise modify the display of
information that has been entered, based on the metrics (one metric
being reputation) that have been collected.
[0034] Embodiments of means for entering information or comments
are later described relative to FIG. 2 and embodiments for
displaying information or comments are later described relative to
FIG. 3. It may be appreciated that the means and method for
collecting metrics, for entering information, and for displaying
information may occur only on the user or client computer or
information appliance, only on a server computer, or distributed
between the two in some manner so that none of these three main
components may be required on any one computing machine. It may
also be appreciated that certain of the components may be optional
to a server component, or to a client component.
[0035] Each of these main components are now described in greater
detail including a description of several non-limiting embodiments,
and with additional descriptions of variations, optional features
and elements, and preferred implementations and/or embodiments.
[0036] First, with regard to the metric collection system,
automated data collection where data is collected without requiring
additional input from a user or contributor, is preferable to
requiring users to input data. The contributor or poster objective
or factually based reputation is one such metric. When it is
desired to collecting data automatically, systems and methods that
can collect lots of relevant data points quickly and with minimal
user effort are advantageously utilized. In cases where it is not
critical that the reputation metrics be recent, use of pre-existing
data may sometimes be possible and may be implemented for some
non-limiting embodiments of the invention. Generally, however, for
systems with large numbers of users for whom metrics have not
already been collected, this "analyze the pre-existing data"
approach is not feasible. Usually collecting, updating, or
otherwise having and using current metrics is advantageous, so that
other embodiments may use this approach.
[0037] Specifically, in the case of financial forecasting systems,
accuracy of predictions is a key performance metric. Accuracy can
be measured as directional accuracy (for example, how often did the
stock go up when the contributing predictor predicted it would go
up) or absolute accuracy (for example, how close was the
contributing predictor's predicted price target to the actual price
the stock achieved). Although there is some data on predictions of
some professional analysts, the data is often incomplete and
generally not as fined-grained as one would desire. Therefore, use
of pre-existing objective data may not be the preferred
implementation for a financial forecasting RBB in many cases,
though certain embodiments of the invention may use such
pre-existing objective data either alone or in addition to other
data. However, in specialized cases (for example serving users who
only care about the posts of established analysts) it could
represent the, or one of several, preferred implementations.
[0038] RBBs are particularly powerful and valuable to financial
forecasting systems when many predictions can be gathered quickly
and easily and the accuracy of these predictions calculated
automatically. The Graphical Forecasting Interface (GFI) described
in referenced related co-pending U.S. patent application Ser. No.
11/______, filed 22 Sep. 2006 (Attorney Docket No. 61117.8004.US01)
entitled Graphical Forecasting Interface, by inventors Craig A.
Kaplan and Calen Lopata, and PCT/US06/______, also filed on 22 Sep.
2006 entitled Graphical Forecasting Interface by inventors Craig A.
Kaplan and Calen Lopata, Attorney Docket No. 61117-8004 W001, which
applications are hereby incorporated by reference, is a method
collecting many data points from users very quickly and easily that
may optionally be utilized with aspects of the Reputation-Based
Boards (RBBs) of the instant application.
[0039] With the aforereferenced GFI or other graphical interface,
thousands of predictions can be stored in a database with a minimal
drain on a user's time. As time passes, the predictions are
automatically checked against the current state of whatever is
being predicted (e.g., stock price) and accuracy is automatically
computed. Thus, based on minimal user effort, a detailed, objective
track record can be automatically generated for each predictor. RBB
then uses this track record to filter posts. A RBB and a graphical
interface (such as for example the referenced patent-pending GFI
graphical forecasting interface or another graphical interface) may
operate synergistically when provided together. Therefore it may be
appreciated that one preferred implementation and embodiment for
forecasting systems may include both a graphical forecasting
interface component and a reputation based board component.
[0040] Second, with regard to entering posts, comments,
recommendations, forecasts, predictions, and/or other information
or data, many options are possible ranging from simple text input
boxes (illustrated in FIG. 2) to sophisticated multi-threaded
bulletin board systems which are available as stand-alone products.
Exemplary computer code is presented in Table 1 by way of example,
as a way that a user may post comments or other information. Table
2 provides by way of example, computer code that may be used to
display and view posted or contributed comments or other
information. The code in Table 3 is exemplary computer program code
for use within a web page to permit users to post and view comments
and operates in conjunction with the code listed in Tables 1 and 2.
This exemplary code provides a non-limiting illustration of how a
simple message board from a financial forecasting system might work
that uses past contributor accuracy as the objective reputation
metric.
[0041] Chat rooms, email, and other forms of asynchronous and
synchronous communication can also be used instead of, or in
addition to, online bulletin or message boards, web sites, and
forums. These aspects and applications of the invention benefit
substantially for the third component, that of ranking, rating, and
filtering. Various filtering mechanisms, means, and method are next
described.
[0042] Consider that a chat room on a financial forecasting site
might incorporates the ability to block communication (or some set
of communication such as postings to a message board) from people
who do not cross a minimum threshold for prediction accuracy.
Similarly, a data feed consisting of forecasts that is streamed to
a ticker (see the above referenced co-pending patent application),
or to an RSS feed, would, in a preferred embodiment of the present
invention, be filtered according to user preferences with regard to
accuracy and/or other criteria that might be important to the user
(e.g., which stocks are in my portfolio or watch list). These and
other optional features may be provided by embodiments of the
present invention.
[0043] In one embodiment, the reputation based board presents a
compilation of relevant content based on the objective reputation
of the contributors. The content may be any content such as a
forecast or prediction, a recommendation, an opinion, a
recommendation, a document, an image, a multimedia content, a
comment or set of comments, an email or other communication, a
message, a message board posting, a bulletin board posting, a forum
posting, a personal profile, a dating profile, a connections
posting, or any other item or content for which an objective
reputation of a contributor, group of contributors, authors,
reviewer(s), or the like may be useful for assessing the value of
that content.
[0044] In one embodiment, the RBB processes the reputations of a
group of contributors of a plurality of postings and uses the
result of the processing to determine which contributor comments
are included in the compilation. In one embodiment, an average,
weighted average, or other algorithmic or statistical
transformation, of the individual reputations may be presented
along with the compiled postings.
[0045] It will be apparent in light of the description provided
here, that the objective reputation of any single contributor may
be used alone or in combination with the objective reputation of
any other single or plurality of contributors, and, that once the
objective contributor reputation information is available it may be
applied to any content without limitation. The objective
reputations may be used for many purposes beyond bulletin
boards.
[0046] For example, in addition to other message board or content
filtering described herein, content of any type may be filtered,
compiled into collections of, highlighted in different colors or
fonts or in different lists or different ways based on reputation
metrics, automatically emailing or streaming comments that cross an
identified reputation threshold, generating an alert in some
fashion when content or material appears or is identified that has
a strong enough reputation associated with it to be of interest to
one or more users or groups of users, automatically deleting
information or archiving information with sufficiently low
reputation metrics, automatically linking to information based on
the reputation associated with the information being linked to
and/or the reputation associated with the information where the
link originates, or other processing, cataloging, notifying, or the
like based on the reputation metric.
[0047] In the context of a financial forecasting system and/or
method, the ability to set accuracy thresholds (for example, a
threshold set to show only predictors with greater than some
specified XX % accuracy) and/or set to sort by accuracy are
features that should be included in a preferred implementation.
[0048] FIG. 3 illustrates very simple sample output of sorting
based on accuracy. The techniques for programming threshold,
filtering, and sorting are well-known in the art, so we do not
describe them in further detail. FIG. 4 (adapted from Slashdot.org)
illustrates a commonly used user interface for filtering controls
that could be part of a preferred implementation of RBB if criteria
included objective poster reputations rather than subjective scores
for posts. It is noted that the Slashdot.org criteria does not
include either objective poster reputations or many other aspects
of the invention set forth herein. The preferred implementation may
also include, without limitation, the ability to
sort/filter/threshold posts by date, by topic, by poster, and by
other categories of interest including accuracy.
[0049] Having now described numerous aspects and embodiment of the
invention including many optional features, attention is directed
to the description of certain selected embodiments that include
particular combinations of features.
[0050] In one embodiment (1) the invention provides a method for
operating a reputation-based communication or content service, the
method comprising: obtaining at least one metric related to a first
user contributor reputation; identifying a communication or content
having an association with the first user contributor; and
processing the communication or content to generate a processed
communication or content based on the obtained objective
contributor reputation.
[0051] In another embodiment (2), the method may further including
processing the communication or content along with other different
communications or content from other different contributors based
at least in part on the objective contributor reputation of one or
of a plurality of contributors.
[0052] In another embodiment (3), the method may further require
that the service is selected from the set of services consisting of
an online bulletin board, an online message board, a chat room, a
forum, a information provision service, a content delivery service,
an email service, an information provision service, a search engine
service, a content delivery service, a communication or content
screening service, a communication or content screening service,
and any combination of these.
[0053] In another embodiment (4), the method may further require
that the obtaining at least one metric related to a first user
contributor reputation comprises the step of collecting the at
least one metric related to a first user contributor
reputation.
[0054] In another embodiment (5), the method may further require
that the method (4) require that the collecting the at least one
metric related to a first user contributor reputation is performed
automatically by the method without a separate conscious input by
the user contributor.
[0055] In another embodiment (6), the method may further require
that the obtaining at least one metric related to a first user
contributor reputation comprises obtaining the at least one metric
related to a first user contributor reputation from an external
source.
[0056] In another embodiment (7), the method may further require
that the identifying of the communication or content comprises: at
least one of: (i) receiving a first communication or content from
the first user contributor; and (ii) identifying a contribution or
content attributed at least in part to the first user
contributor.
[0057] In another embodiment (8), the method may further require
that the identifying of a communication or content having an
association with the first user contributor comprises
[0058] In another embodiment (9), the method may further require
sending a second communication to a user that includes the
generated processed communication or content or portion
thereof.
[0059] In another embodiment (10), the method may further require:
obtaining at least one metric related to a plurality of different
user contributor reputations; identifying a communication or
content having an association with each of the plurality of user
contributors; and processing the plurality of communications or
contents to generate a processed communication or content based on
the obtained objective contributor reputation for the plurality of
different user contributors.
[0060] In another embodiment (11), the method may further require
that the processing based on objective reputation comprises a
processing selected from the set consisting of filtering, sorting,
ordering, screening, compiling, grouping, deleting, flagging,
hiding, highlighting, promoting, and any combination of these based
on objective reputation of a contributor or a plurality of
contributors.
[0061] In another embodiment (12), the method (11) may further
require that wherein the processing may be different for different
contributors or for different groups of contributors.
[0062] In another embodiment (13), the method may further require
that the processing based on objective reputation includes a
processing selected from the set consisting of: filtering to
include some items and not others based on objective reputation of
the contributor or group of contributors, filtering based on
objective reputation of the contributor or group of contributors,
filtering to exclude some items and not others based on objective
reputation of the contributor or group of contributors, compiling a
set of relevant content based on objective reputation of the
contributor or group of contributors, ordering based on objective
reputation of the contributor or group of contributors, ordering
from low to high based on objective reputation of the contributor
or group of contributors, ordering from high to low based on
objective reputation of the contributor or group of contributors,
selecting or not selecting based on objective reputation of the
contributor or group of contributors, processing based on objective
reputation of the contributor or group of contributors, generating
derivative objective reputation data based on objective reputation
of the contributor or group of contributors, and any combination of
these.
[0063] In another embodiment (14), the method may further require
that the service is a communication forum selected from the set of
forums consisting of a network site, an Intranet site, an Internet
site, a world wide web site, an electronic mail or email, an
interactive electronic bulletin board, an interactive electronic
message board, an online information exchange, a set of email or
comment threads, an online interactive stock prediction forum, an
online forum, and any combination of these.
[0064] In another embodiment (15), the method may further require
that the reputation metric comprises a factually based objective
contributor reputation established in the same field of endeavor as
the contribution being communicated.
[0065] In another embodiment (16), the method may further require
that the objective contributor reputation comprises a historical
accuracy-based reputation.
[0066] In another embodiment (17), the method may further require
that the historical accuracy-based reputation is for a contribution
in the same field as the reputation was established.
[0067] In another embodiment (18), the method may further require
that the step of collecting objective metrics, comprises collective
objective metrics automatically without compelling a user take
separate actions to provide objective metrics of information from
which objective metrics are derived.
[0068] In another embodiment (19), the method may further require
matching these reputation metrics closely to the topic of the
particular communication forum.
[0069] In another embodiment (20), the method may further require
filtering contributor postings with a predetermined objective
accuracy and without a conscious human input contribution relative
to a filtering metric.
[0070] In another embodiment (21), the method may further require
automatically tracking the accuracy of contributors who provide an
online prediction or forecast of an element and generating a
prediction accuracy result by comparing the prediction of the
element with the actual value of the element at the predicted time
and date, and automatically generating a prediction accuracy for
the contributor based on that comparison.
[0071] In another embodiment (22), the method may further require
that the element is an online stock price prediction.
[0072] In another embodiment (23), the method may further require
that reputation metrics are be subjected to aging or other
refinement so that recent objective history is given a greater
objective weight or older performance may be discounted or not
considered at all.
[0073] In another embodiment (24), the method may further require
that collected or otherwise directly or indirectly available
reputation metrics are processed to make them more useful.
[0074] In another embodiment (25), the method may further require
that the processing to make them more useful comprises applying a
statistical processing to a least one objective reputation
metric.
[0075] In another embodiment (26), the method may further require
that the applied statistical processing is selected from the set of
statistical processing comprising: computing a weighted average
over time, normalizing the reputation or plurality of reputations
so that one contributor's reputation can be compared with another
contributor's reputation according to some defined comparison
criteria.
[0076] In another embodiment (27), the method may further require
that the defined comparison criteria comprises an objective
comparison criteria.
[0077] In another embodiment (27), the method may further require
that the objective reputations comprise raw reputations, processed
reputations, or any combination of raw reputations and processed
reputations.
[0078] In another embodiment (28), the method may further require
that the method further includes filtering or automatically
selecting contributions to be seen or presented to a user based on
an objective metric or combination of a plurality of metrics.
[0079] In another embodiment, the invention provides a system for
providing a reputation processed based on-line communication or
content, the system comprising: a contributor reputation metric
collection component; a communication or content medium
identification component; and a communication or content reputation
processing component.
[0080] Various different embodiments of the system may incorporate
components, functional blocks, computer program software, or other
means for implementing the steps of the inventive method described
herein.
[0081] In another embodiment (30), the system may further require
that the collection component comprises a automatic collection
component for collecting the reputation metric related to a
contributor reputation automatically without a separate conscious
input by a user contributor.
[0082] In another embodiment (31), the system (30) may further
require that the at least one reputation metric is obtained from an
external source.
[0083] In another embodiment (32), the system may further require
that the contributor reputation metric identification component
includes means for identifying of the communication or content
selected from the set consisting of: (i) receiving a first
communication or content from the first user contributor; and (ii)
identifying a contribution or content attributed at least in part
to the first user contributor.
[0084] In another embodiment (33), the system (32) may further
require that the communication or content reputation processing
component comprises a processing unit adapted for processing
selected from the set of processing schemes consisting of
filtering, sorting, ordering, screening, compiling, grouping,
deleting, flagging, hiding, highlighting, promoting, and any
combination of these based on objective reputation of a contributor
or a plurality of contributors.
[0085] In another embodiment (34), the system (33) may further
require that the processing may be different for different
contributors or for different groups of contributors.
[0086] In another embodiment (35), the system (34) may further
require that the communication or content reputation processing
component comprises a processing unit adapted for processing
selected from the set of processing schemes consisting of
filtering, sorting, ordering, screening, compiling, grouping,
deleting, flagging, hiding, highlighting, promoting, and any
combination of these based on objective reputation of a contributor
or a plurality of contributors.
[0087] In another embodiment (36), the system may further require
that the communication or content medium component is selected from
the set consisting of a network site, an Intranet site, an Internet
site, a world wide web site, an electronic mail or email, an
interactive electronic bulletin board, an interactive electronic
message board, an online information exchange, a set of email or
comment threads, an online interactive stock prediction forum, an
online forum, and any combination of these.
[0088] In another embodiment (37), the system may further require
that the communication or content medium component further includes
(a) means and for entering information, and (b) means for
displaying information.
[0089] In another embodiment (38), the system may further require
that the communication or content filtering component provides
means for sorting, limiting, compiling, or otherwise modifying
{other wise modifying is good, otherwise it sounds like only
limiting and filtering and we are missing other forms of processing
like compiling} the display of information that has been entered
based on metrics that have been collected.
[0090] In another aspect, the invention provides a communication or
content processed according to the method and or by a system as
described.
[0091] In another aspect, the invention provides a computer program
product stored in an electronically accessible media for altering
the operation of a computer system or computer network, the
computer program product including executable computer program
instructions for causing the computer to generate a processed
reputation-based communication or content and comprising
instructions for: obtaining at least one metric related to a first
user contributor reputation; identifying a communication or content
having an association with the first user contributor; and
processing the communication or content to generate a processed
communication or content based on the obtained objective
contributor reputation.
[0092] In another embodiment, the computer program and computer
program product may provide program components to implement any of
the steps and/or features of the described inventive method, and be
implemented on a computer or on a plurality of computers to achieve
a technical effect by altering the otherwise conventional operation
of the computer or plurality of computers.
[0093] In another aspect, the invention provides a business method
for operating a reputation-based communication or content provision
service, the business method comprising: obtaining at least one
metric related to a first user contributor reputation; identifying
a communication or content having an association with the first
user contributor; processing the communication or content to
generate a processed communication or content based on the obtained
objective contributor reputation; providing the processed
communication or content to a subscriber; and receiving a
remuneration from the subscriber in exchange for the provided
processed communication or content.
[0094] In another embodiment, the business method may further
require that the remuneration is a financial remuneration, a
service remuneration, a commission remuneration, a referral
remuneration, or any combination of these.
[0095] As used herein, the term"embodiment" means an embodiment
that serves to illustrate by way of example but not limitation.
[0096] It will be appreciated to those skilled in the art that the
preceding examples and embodiments are exemplary and not limiting
to the scope of the present invention. It is intended that all
permutations, enhancements, equivalents, and improvements thereto
that are apparent to those skilled in the art upon a reading of the
specification and a study of the drawings are included within the
true spirit and scope of the present invention. It is therefore
intended that the following appended claims include all such
modifications, permutations and equivalents as fall within the true
spirit and scope of the present invention.
COPYRIGHT NOTICE
[0097] Contained herein is material that is subject to copyright
protection. The copyright owner has no objection to the facsimile
reproduction of the patent disclosure by any person as it appears
in the Patent and Trademark Office patent files or records, but
otherwise reserves all rights to the copyright whatsoever
TABLE-US-00001 TABLE 1 Exemplary Code for User Comment (File Name:
comment.asp) <% Option Explicit %> <!--#include
virtual="/asp/SystemFunctions.asp"--> <!--#include
virtual="/asp/FinWinFunctions.asp"--> <!--#include
virtual="/asp/DateTimeFunctions.asp"--> <% ` Copyright 2005
iQ Company Dim Global_Database_Connection Set
Global_Database_Connection =
Server.CreateObject("ADODB.connection")
Global_Database_Connection.Open Application("DSN") ` This wasn't
working ?!?!? `SafeDate(Request("ForecastDate")), .sub.--
SaveForecastComment .sub.-- Global_Database_Connection, .sub.--
Session("RegisteredUserID"), .sub.-- CData(Session("Login"),
"string"), .sub.-- Cdata(Request("StarRating"), "string"), .sub.--
Cdata(Request("Symbol"), "string"), .sub.-- NextForecastDate( ),
.sub.-- Cdata(Request("BaselinePrice"), "double"), .sub.--
Cdata(Request("DirectionalForecastUp"), "string"), .sub.--
Cdata(Request("Comment"), "string")
Global_Database_Connection.Close Set Global_Database_Connection =
Nothing If Request("action") = "ajax" Then Response.Write
"comment_area|Thank you, your comment has been saved." Response.end
End If StartHTML "Comment Saved", "", "", "" %> <p>
<br> <p align=center><font size=+1>Comment saved
- thank you for contributing! <br><br><a
href="<%=Trim(Request("ReturnPage"))%>">Back</a></font&-
gt;</p> <% EndHTML Sub SaveForecastComment(objConn,
UserID, UserName, StarRating, Symbol, .sub.-- MyForecastDate,
BaselinePrice, DirectionalForecastUp, Comment) Dim ForecastDate,
SQL ForecastDate = "`" & Replace(MyForecastDate,"`", "\``)
& "`" SQL = "If Not Exists(Select Top 1 CommentID From
tblDirectionalForecastComments Where UserID = " & .sub.--
UserID & " And ForecastDate = " & ForecastDate & " And
Symbol = " & Symbol & .sub.-- ") Insert Into
tblDirectionalForecastComments " & .sub.-- "(UserID, UserName,
StarRating, Symbol, ForecastDate, " & .sub.-- " BaselinePrice,
DirectionalForecastUp, CreateDate, Comment) Values (" & .sub.--
UserID & ", " & UserName & ", " & StarRating &
", " & Symbol & ", " & ForecastDate & ", " &
.sub.-- BaselinePrice & ", " & DirectionalForecastUp &
", GETDATE( ), " & Comment & .sub.-- ") ELSE Update
tblDirectionalForecastComments Set Comment = " & .sub.--
Comment & ", BaselinePrice = " & BaselinePrice &
.sub.-- ", DirectionalForecastUp = " & DirectionalForecastUp
& ", StarRating = " & StarRating & " WHERE UserID = "
& .sub.-- UserID & " And ForecastDate = " &
ForecastDate & " And Symbol = " & Symbol objConn.Execute
SQL End Sub %>
[0098] TABLE-US-00002 TABLE 2 Exemplary Code for Viewing User
Comments (File Name: Comment_view.asp) <% Option Explicit %>
<!--#include virtual="/asp/SystemFunctions.asp"-->
<!--#include virtual="/asp/DisplayFunctions.asp"-->
<!--#include virtual="/asp/FinWinFunctions.asp"--> <% `
Copyright 2005 iQ Company Dim Symbol, ForecastDate Dim
Global_Database_Connection Set Global_Database_Connection =
Server.CreateObject("ADODB.connection")
Global_Database_Connection.Open Application("DSN") Symbol =
GetSymbolListFromInputList(Request("Symbol")) ForecastDate =
Request("ForecastDate") StartHTML "Comments on " & Symbol, "",
"", "" `PrintHeader DisplayAllComments Global_Database_Connection,
Symbol, ForecastDate `PrintFooter EndHTML Function
DisplayAllComments(objConn, Symbol, ForecastDate) Dim rst,
ForecastWeekday, NumStars, AccuracyHTML ForecastWeekday =
DisplayWeekday(ForecastDate) Set rst = objConn.Execute("Select
tblDirectionalForecastComments.*, " & .sub.-- " Case When
DirectionalForecastUp Is NULL Then `No Opinion` " & .sub.-- "
When DirectionalForecastUp = 1 Then `UP` " & .sub.-- " Else
`DOWN` End " & .sub.-- "as DirectionalForecastText From
tblDirectionalForecastComments Where Symbol = `" & .sub.--
Symbol & "` And ForecastDate = `" & ForecastDate & "`
Order By StarRating Desc") If Not rst.EOF Then %> <p>
<table border=0 cellpadding=0 cellspacing=5> <% If
Session("RegisteredUserID") = "" Then %> <tr><td
colspan=3><font size=-1>Everyone can view comments, but to
post your own comments please <a href="javascript:window.close(
);">close this window</a> and log
in.<br></font></td></tr> <% End If %>
<tr> <td><font
size=-1><b>Comment</b></font></td>
<td><font size=-1><b>Forecast for
<%=ForecastWeekday%></b></font></td>
<td><font size=-1><b>Past
Accuracy</b></font></td> </tr> <% Do
While Not rst.EOF NumStars = 1+rst("StarRating") If NumStars = 0
Then AccuracyHTML = "Unrated" Else AccuracyHTML = GetStarsHTML(5,
1+rst("StarRating"),False, "") End If %> <tr>
<td><fontsize=-1><%=Left(rst("UserName"),
InStr(rst("UserName"), "@")-1)%> said,
"<%=rst("Comment")%>"</font> <br><font
size=-2>[<%=FormatDateTime(rst("CreateDate"), vbLongDate)
& " " & FormatDateTime(rst("CreateDate"), vbLongTime)%>
ET]</font></td> <td><font
size=-1><%=rst("DirectionalForecastText")%> from
<%=DisplayDouble(rst("BaselinePrice"))%></font></td>
<td><font
size=-1><%=AccuracyHTML%></font></td>
</tr> <% rst.MoveNext Loop %> </table></p>
<% Else Response.Write "<font size=+2>No comments for "
& ForecastWeekday & "'s close of " & Symbol &
".</font>" End If End Function %>
[0099] TABLE-US-00003 TABLE 3 Exemplary Code for use within a web
page to permit users to post and view comments (File Name: Comments
Functionality.asp) <% ` Copyright 2005 iQ Company `ASP Code
========================================
================================================= ` For use within
a page where you want users to be able to post and view comments. `
Uses comment.asp and comment_view.asp ` Generates javascript for
inclusion within HTML <head> tags. Function
GetCommentJavascript(Symbol, ForecastDate, BaselinePrice,
DirectionalForecastUp, StarRating) Dim QueryString QueryString =
"Symbol=" & Server.URLEncode(Symbol) & .sub.--
"&ForecastDate=" & Server.URLEncode(ForecastDate) &
.sub.-- "&BaselinePrice=" & Server.URLEncode(BaselinePrice)
& .sub.-- "&DirectionalForecastUp=" &
Server.URLEncode(DirectionalForecastUp) & .sub.--
"&StarRating=" & Server.URLEncode(StarRating) & .sub.--
"&action=ajax" GetCommentJavascript = "<SCRIPT
LANGUAGE=""JavaScript""> " & .sub.-- vbCrLf & "<!-- "
& .sub.-- vbCrLf & "function URLencode(sStr) {" &
.sub.-- vbCrLf & " return escape(sStr)." & .sub.-- vbCrLf
& " replace(/\+/g, `%2B`)." & .sub.-- vbCrLf & "
replace(/\""/g,`%22`)." & .sub.-- vbCrLf & " replace(/\'/g,
`%27`)." & .sub.-- vbCrLf & " replace(/\//g,`%2F`);" &
.sub.-- vbCrLf & " }" & .sub.-- vbCrLf & "function
createRequestObject( ) {" & .sub.-- vbCrLf & " var ro;"
& .sub.-- vbCrLf & " var browser = navigator.appName;"
& .sub.-- vbCrLf & " if(browser == ""Microsoft Internet
Explorer""){" & .sub.-- vbCrLf & " ro = new
ActiveXObject(""Microsoft.XMLHTTP"");" & .sub.-- vbCrLf & "
}else{" & .sub.-- vbCrLf & " ro = new XMLHttpRequest( );"
& .sub.-- vbCrLf & " }" & .sub.-- vbCrLf & " return
ro;" & .sub.-- vbCrLf & "}" & .sub.-- vbCrLf &
""& .sub.-- vbCrLf & "var http = createRequestObject( );"
& .sub.-- vbCrLf & "" & .sub.-- vbCrLf & "function
sndReq(comment) {" & .sub.-- vbCrLf & " http.open(`get`,
`comment.asp?" & QueryString &
"&comment=`+URLencode(comment));" & .sub.-- vbCrLf & "
http.onreadystatechange = handleResponse;" & .sub.-- vbCrLf
& " http.send(null);" & .sub.-- vbCrLf & "}" &
.sub.-- vbCrLf & "" & .sub.-- vbCrLf & "function
handleResponse( ) {" & .sub.-- vbCrLf & "
if(http.readyState == 4){" & .sub.-- vbCrLf & " var
response = http.responseText;" & .sub.-- vbCrLf & " var
update = new Array( );" & .sub.-- vbCrLf & "" & .sub.--
vbCrLf & " if(response.indexOf(`|` != -1)) {" & .sub.--
vbCrLf & " update = response.split(`|`);" & .sub.-- vbCrLf
& " document.getElementById(update[0]).innerHTML = update[1];"
& .sub.-- vbCrLf & " }" & .sub.-- vbCrLf & " }"
& .sub.-- vbCrLf & "}" & .sub.-- vbCrLf & "//-->
" & .sub.-- vbCrLf & "</script>" End Function `
Generates comment form Function GetCommentArea(objConn,
RegisteredUserID, Symbol, ForecastDate, BaselinePrice,
UserPrediction, StarRating) Dim MyHTML, rst, NumComments,
CommentPlural Set rst = objConn.Execute("Select Count(*) as
TheTotal From tblDirectionalForecastComments where Symbol = `"
Symbol & "` And ForecastDate = `" & ForecastDate & "`")
NuMComments = rst("TheTotal") Set rst = Nothing If RegisteredUserID
<> "" Then MyHTML = GetDynamicCommentForm(
SimulateThisPageLink( ), Symbol, ForecastDate, BaselinePrice,
UserForecast, ConvertDirectionalToBitForecast(UserPrediction),
StarRating ) End If If NuMComments > 0 Then CommentPlural = ""
If NumComments <> 1 Then CommentPlural = "s" End If MyHTML =
MyHTML & "<center><Font size=-1>" & .sub.--
PopupWindowLink("View " & NumComments & " comment" &
CommentPlural & " on " & Symbol, .sub.--
"/help/help.asp?text=" & Server.URLEncode("Comments on " &
Symbol) & "&src=" &
Server.URLEncode("/comment_view.asp?Symbol=" &
Server.URLEncode(Symbol) & "&ForecastDate=" &
Server.URLEncode(ForecastDate)), 500, 400) & .sub.--
"</font></center>" End If GetCommentArea = MyHTML End
Function ` Converts text forecast to bit forecast (for database
storage) Function ConvertDirectionalToBitForecast(UserPrediction)
If UserPrediction = "UP" Then ConvertDirectionalToBitForecast = 1
ElseIF UserPrediction = "DOWN" Then ConvertDirectionalToBitForecast
= 0 Else ConvertDirectionalToBitForecast = "" End If End Function
%>
* * * * *
References