Techniques are described for analyzing user-supplied information and/or predicting future aspects of additional information that will be supplied by users. The analyzed information may include distributed group discussions involving numerous users, occurring via user comments and other content items supplied to social networking site(s) and/or other sources. Analysis of user-supplied information may, for example, include determining particular topics and/or categories of interest during one or more time periods and quantifying corresponding amounts of user interest; determining trends for, relevant terms and attributes for, and inter-relationships between the topics and categories; predicting future amounts of user interest in the topics and categories; tracking user interactions with information about the topics and/or categories; and taking further actions based on the analyzed and/or predicted information.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A computer-implemented method comprising: analyzing, by a configured computing system of a group discussion analysis and prediction service, a plurality of textual comments to identify a plurality of topics that are each mentioned in contents of one or more of the plurality of textual comments, the plurality of textual comments being supplied by human users during a specified prior time period; generating, by the configured computing system, a plurality of comment groups based on the identified topics, each of the generated comment groups being associated with one of the identified topics and including one or more of the plurality of textual comments that have contents mentioning the associated identified topic; identifying, by the configured computing system, a subset of the plurality of textual comments that are associated with a specified content category based on contents of the textual comments of the identified subset, the textual comments of the identified subset being included in multiple of the generated comment groups; determining, by the configured computing system, a subset of the multiple generated comment groups that correspond to the specified content category for the specified prior time period; discovering, by the configured computing system, additional content categories that are related to the specified content category, wherein each of the additional content categories corresponds to the topic of at least one of the determined subset of comment groups; and providing, by the configured computing system, indications of the determined additional content categories that are related to the specified content category. 2. The computer-implemented method of claim 1 further comprising: determining, by the configured computing system, multiple terms of interest that are distinct from the plurality of topics, and assigning each of the multiple terms to one of multiple graph axes; determining, by the configured computing system, and for each of at least some of the plurality of topics, a relevance of one of the generated comment groups associated with the topic to the multiple terms based at least in part on the textual comments included in the one generated comment group; and providing, by the configured computing system, information to initiate display of a multi-dimensional graph that includes the multiple graph axes and that includes visual indicators for multiple of the at least some topics on the multi-dimensional graph, wherein a position of each of the multiple topics on the displayed multi-dimensional graph is based on the determined relevance of the one generated comment group associated with the topic to the multiple terms and is based on the assignment of the multiple terms to the multiple graph axes, to enable a visual determination from the displayed multi-dimensional graph of relative relevance of the multiple topics to the multiple terms. 3. The computer-implemented method of claim 1 further comprising providing, by the configured computing system, indications of multiple topics determined to correspond to the specified content category for the specified prior time period, the multiple topics including, for each of the generated comment groups in the determined subset, the associated identified topic for the generated comment group. 4. The computer-implemented method of claim 1 wherein the determining of the subset includes at least one of excluding at least one first comment group whose included textual comments appear in the identified subset less than a determined minimum threshold or of excluding at least one second comment group whose included textual comments appear in the identified subset more than a determined maximum threshold. 5. The computer-implemented method of claim 1 further comprising: determining, by the configured computing system, and for each of the comment groups of the determined subset, a quantity of the textual comments included in the comment group; predicting, by the configured computing system, and for each of the comment groups of the determined subset, an expected quantity of future textual comments associated with the identified topic for the comment group that will be supplied by human users during a future time period, the predicting being based in part on the determined quantity for the comment group; and providing, by the configured computing system, an indication of the predicted expected quantity of future textual comments for one or more of the comment groups of the determined sub set. 6. The computer-implemented method of claim 1 further comprising: determining, by the configured computing system, and for each of the comment groups of the determined subset, a quantity of the textual comments included in the comment group; predicting, by the configured computing system, an expected quantity of future textual comments associated with the specified content category that will be supplied by human users during a future time period, the predicting being based in part on a combination of the determined quantities for the comment groups of the determined subset; and providing, by the configured computing system, an indication of the predicted expected quantity of future textual comments for the specified content category. 7. The computer-implemented method of claim 1 wherein the plurality of textual comments are supplied by a plurality of human users at multiple geographical locations, and wherein the method further comprises: determining, by the configured computing system, and for one of the comment groups of the determined subset, distinct subsets of the textual comments included in the one comment group that are associated with each of the multiple geographical locations; determining, by the configured computing system, and for each of the multiple geographical locations, a quantity of the textual comments included in the subset associated with the geographical location; and providing, by the configured computing system, information about the determined quantity for each of one or more of the multiple geographical locations. 8. The computer-implemented method of claim 1 wherein the plurality of textual comments are posts supplied by a plurality of human users to one or more social networking services, and wherein the method further comprises: determining, by the configured computing system, and for one of the comment groups of the determined subset, distinct subsets of the textual comments included in the one comment group that are associated with each of the plurality of human users; determining, by the configured computing system, and for each of the plurality of human users, a quantity of the textual comments included in the subset associated with the human user; and providing, by the configured computing system, information about the determined quantity for each of one or more of the plurality of human users. 9. The computer-implemented method of claim 1 wherein the plurality of textual comments are supplied by the human users to a plurality of information sources, and wherein the method further comprises: determining, by the configured computing system, and for one of the comment groups of the determined subset, distinct subsets of the textual comments included in the one comment group that are associated with each of the plurality of information sources; determining, by the configured computing system, and for each of the plurality of information sources, a quantity of the textual comments included in the subset associated with the information source; and providing, by the configured computing system, information about the determined quantity for each of one or more of the plurality of information sources. 10. The computer-implemented method of claim 1 further comprising: determining, by the configured computing system, and for one of the comment groups of the determined subset, a quantity of the textual comments included in the one comment group; determining, by the configured computing system and based at least in part on the determined quantity, one or more types of information to make available corresponding to at least one of the specified content category and the identified topic associated with the one comment group; and supplying, by the configured computing system, one or more additional textual comments that are available to the human users and that have contents corresponding to the determined one or more types of information. 11. The computer-implemented method of claim 10 wherein the plurality of textual comments are part of user posts to one or more social networking services by the human users, and wherein the supplying of the one or more additional textual comments includes supplying the additional textual comments to at least one of the social networking services as additional posts. 12. The computer-implemented method of claim 1 further comprising: determining, for each of one or more additional prior time periods, a plurality of comment groups that have corresponding topics for the specified content category for the additional prior time period and that, wherein the corresponding topics for the determined plurality of comment groups of at least some of the additional prior time periods are distinct from the plurality of topics determined to correspond to the specified content category for the specified prior time period; and providing indications of one or more topic changes for the specified content category between the specified prior time period and one or more of the additional prior time periods. 13. The computer-implemented method of claim 1 further comprising: receiving, by the configured computing system, information about a succession of multiple content categories that one or more users select; and providing, by the configured computing system, information to initiate display of information to at least one user about the succession of the multiple content categories. 14. The computer-implemented method of claim 13 wherein the receiving of the information about the succession of the multiple content categories includes: tracking, by the configured computing system, interactions of a plurality of users with a plurality of content categories; and analyzing, by the configured computing system, the tracked interactions to identify the succession of multiple content categories, wherein the multiple content categories are a subset of the plurality of content categories, and wherein the one or more users include at least some of the plurality of users. 15. The computer-implemented method of claim 1 further comprising: receiving, by the configured computing system, information about a succession of multiple comment groups that one or more users select; and providing, by the configured computing system, information to initiate display of information to at least one user about the succession of the multiple comment groups. 16. The computer-implemented method of claim 1 further comprising: receiving, by the configured computing system, a request from a user to display selected information that relates to at least one of one or more comment groups or one or more content categories; determining, by the configured computing system, one or more pieces of promotional content that are not included in the selected information and that are relevant for the selected information; and providing, by the configured computing system, information to initiate display to the user of the selected information and of at least one of the one or more pieces of promotional content. 17. The computer-implemented method of claim 1 further comprising: analyzing, by the configured computing system and for each of the plurality of comment groups, the one or more textual comments included in the comment group to determine one or more relevant attributes for the comment group that are distinct from the associated topic for the comment group; and providing, by the configured computing system, information about the determined one or more relevant attributes for one or more of the plurality of comment groups. 18. The computer-implemented method of claim 17 further comprising determining, by the configured computing system, one or more inter-relationships that are each between two or more comment groups associated with two or more content categories, wherein the determining of each of the inter-relationships is based at least in part on the determined one or more relevant attributes for each of the two or more comment groups of the inter-relationship, and wherein the providing of the information about the determined one or more relevant attributes includes providing information about at least one of the determined inter-relationships. 19. The computer-implemented method of claim 18 wherein at least some of the determined relevant attributes for at least some of the plurality of comment groups are terms included in contents of the plurality of textual comments, and wherein the method further comprises displaying, by the configured computing system, information about at least one of the determined inter-relationships to at least one user. 20. The computer-implemented method of claim 17 wherein the providing of the information about the determined one or more relevant attributes includes displaying, by the configured computing system, information to at least one user about the determined one or more relevant attributes for the one or more comment groups. 21. The computer-implemented method of claim 1 further comprising: analyzing, by the configured computing system and for one or more of the content categories, information about the textual comments included in the subset of multiple generated comment groups corresponding to the one content category to determine one or more relevant attributes for the one content category that are distinct from any definition terms for the one content category; and providing, by the configured computing system, information about the determined one or more relevant attributes for the one content category. 22. The computer-implemented method of claim 21 wherein at least one of the determined relevant attributes for the one content category is a term included in contents of the textual comments included in the subset of multiple generated comment groups corresponding to the one content category, and wherein the method further comprises: analyzing, by the configured computing system and for one or more of the plurality of comment groups that are not in the subset of multiple generated comment groups corresponding to the one content category, the one or more textual comments included in the comment group to determine one or more relevant attributes for the comment group that are distinct from the associated topic for the comment group; and determining, by the configured computing system, one or more inter-relationships that are each between the one content category and at least one of the one or more comment groups that are not in the subset of multiple generated comment groups corresponding to the one content category, wherein the determining of each of the inter-relationships is based at least in part on the determined relevant attributes for the one content category and on the determined one or more relevant attributes for the at least one comment group of the inter-relationship, and wherein the providing of the information about the determined one or more relevant attributes for the one content category includes displaying, by the configured computing system, information to at least one user about at least one of the determined one or more relevant attributes for the one content category or of the determined one or more inter-relationships. 23. The computer-implemented method of claim 1 wherein the specified content category is indicated by a client of the group discussion analysis and prediction service, and wherein the providing of the indications of the determined additional content categories includes providing information to the client in accordance with criteria specified by the client. 24. The computer-implemented method of claim 1 wherein the identified plurality of topics are each at least one of a term, of a phrase, or of a hashtag. 25. A non-transitory computer-readable medium having stored contents that configure a computing system to perform a method, the method comprising: obtaining, by the configured computing system, information about a distributed group discussion that involves a plurality of users submitting a plurality of textual comments for the distributed group discussion, wherein the obtained information indicates a plurality of topics mentioned in contents of the plurality of textual comments, and wherein each topic is associated with one or more of the plurality of textual comments whose contents mention the topic; determining, by the configured computing system, multiple terms of interest that are distinct from the plurality of topics, and assigning each of the multiple terms to one of multiple graph axes; determining, by the configured computing system, and for each of at least some of the plurality of topics, a relevance of the topic to the multiple terms based at least in part on the textual comments associated with the topic; and providing, by the configured computing system, information to initiate display of a multi-dimensional graph that includes the multiple graph axes and that includes visual indicators for multiple of the at least some topics on the multi-dimensional graph, wherein a position of each of the multiple topics on the displayed multi-dimensional graph is based on the determined relevance of the topic to the multiple terms and is based on the assignment of the multiple terms to the multiple graph axes, to enable a visual determination from the displayed multi-dimensional graph of relative relevance of the multiple topics to the multiple terms. 26. The non-transitory computer-readable medium of claim 25 wherein the configured computing system is part of a group discussion analysis service, wherein the computer-readable medium is a memory of the configured computing system, and wherein the stored contents are software instructions that, when executed, program the configured computing system to perform the method. 27. The non-transitory computer-readable medium of claim 26 wherein the providing of the information to initiate the display of the multi-dimensional graph includes providing the information to a client device of a user of the group discussion analysis service, and wherein display of the multi-dimensional graph occurs on the client device for the user. 28. The non-transitory computer-readable medium of claim 27 wherein the visual indicators for the multiple topics that are included on the displayed multi-dimensional graph are each selectable by the user, and wherein the method further comprises: receiving, by the configured computing system, an indication of one of the multiple topics selected by the user via an interaction with the visual indicator for the selected one topic; and providing, by the configured computing system and in response to the received indication of the selected one topic, additional information for display to the user regarding the selected one topic, wherein the additional information includes at least one of information about the textual comments associated with the selected one topic, information about one or more attributes determined to be relevant to the selected one topic based at least in part on an analysis of the textual comments associated with the selected one topic, or information about one or more inter-relationships determined between the selected one topic and one or more other topics of the plurality based at least in part on an analysis of information about the selected one topic and about the one or more other topics. 29. The non-transitory computer-readable medium of claim 27 wherein the determining of the multiple terms of interest includes receiving, by the configured computing system, selections from the user of the multiple terms. 30. The non-transitory computer-readable medium of claim 27 wherein the assigning of each of the multiple terms to one of multiple graph axes includes receiving, by the configured computing system, indications from the user of a type of multi-dimensional graph and of, for each of the multiple terms, one of the multiple graph axes to which the term is to be assigned. 31. The non-transitory computer-readable medium of claim 27 wherein the method further comprises, before the providing of the information: receiving, by the configured computing system, one or more criteria from the user for use in selecting a subset of the at least some topics to display on the multi-dimensional graph; and selecting, by the configured computing system, the multiple topics based at least in part on the one or more criteria, wherein the multiple topics are a subset of the at least some topics. 32. The non-transitory computer-readable medium of claim 27 wherein the method further comprises, after the providing of the information: receiving, by the configured computing system, one or more additional terms of interest from the user; determining, by the configured computing system, and for each of the multiple topics, a relevance of the topic to the one or more additional terms; and providing, by the configured computing system, additional information to initiate an updated display of the multi-dimensional graph in which the one or more additional terms are each assigned to one of the multiple graph axes and in which the positions of the visual indicators for the multiple topics are updated to reflect the determined relevances of the multiple topics to the one or more additional terms. 33. The non-transitory computer-readable medium of claim 27 wherein the method further comprises, under control of the client device, receiving the provided information, and displaying the multi-dimensional graph to the user on one or more display screens associated with the client device. 34. The non-transitory computer-readable medium of claim 25 wherein each of the multiple graph axes has a single assigned term and includes a plurality of positions that each corresponds to a distinct degree of relevance with respect to the single assigned term, wherein the determining of the relevance of each of the at least some topics to the multiple terms includes, for each of the at least some topics and each of the multiple terms, determining a relevance score of the topic to the term that reflects a degree of relevance of the term to the topic, and wherein, for each of the multiple topics, the position of the visual indicator for the topic is selected for each of the multiple graph axes to correspond to the degree of relevance for the topic to the single assigned term for the graph axis. 35. The non-transitory computer-readable medium of claim 25 wherein one of the multiple graph axes is assigned at least two of the multiple terms and includes a plurality of positions that each corresponds to a distinct degree of relevance with respect to a combination of the assigned at least two terms, wherein the determining of the relevance of each of the at least some topics to the multiple terms includes, for each of the at least some topics and the assigned at least two terms, determining degree of relevance of the topic to a combination of the assigned at least two terms, and wherein, for each of the multiple topics, the position of the visual indicator for the topic is selected for the one graph axis to correspond to the degree of relevance for the topic to the combination of the assigned at least two terms. 36. The non-transitory computer-readable medium of claim 25 wherein one of the multiple graph axes is assigned to one or more attributes distinct from the multiple terms and includes a plurality of positions that each corresponds to a distinct degree of relevance with respect to the assigned one or more attributes, wherein the determining of the relevance of each of the at least some topics to the multiple terms further includes, for each of the at least some topics, determining a degree of relevance of the topic to the assigned one or more attributes, and wherein, for each of the multiple topics, the position of the visual indicator for the topic is selected for the one graph axis to correspond to the degree of relevance for the topic to the assigned one or more attributes. 37. The non-transitory computer-readable medium of claim 25 wherein the plurality of textual comments are supplied by the plurality of users during a specified prior time period, and wherein the obtaining of the information about the distributed group discussion includes: analyzing, by the configured computing system, the plurality of textual comments to identify the plurality of topics; generating, by the configured computing system, a plurality of comment groups based on the identified plurality of topics, wherein each of the generated comment groups is associated with one of the identified topics and includes one or more of the plurality of textual comments that have contents mentioning the associated identified topic; identifying, by the configured computing system and for each of a plurality of specified content categories, a distinct subset of the plurality of textual comments that are associated with the specified content category based on contents of the textual comments of the identified subset, the textual comments of the identified subset being included in multiple of the generated comment groups; and determining, by the configured computing system and for each of the plurality of specified content categories, a distinct subset of the multiple generated comment groups that correspond to the specified content category for the specified prior time period, and wherein the visual indicators for the multiple topics correspond to multiple comment groups that are a subset of the plurality of comment groups, wherein each of the multiple comment groups is associated with one of the multiple topics. 38. The non-transitory computer-readable medium of claim 37 wherein the multiple comment groups are assigned to multiple content categories of the plurality of specified content categories. 39. The non-transitory computer-readable medium of claim 38 wherein the plurality of content categories are specified by a client of a group discussion analysis service, and wherein the providing of the information is performed in response to a request from the client, to further enable a visual determination by the client from the displayed multi-dimensional graph of relative relevance of the multiple comment groups from the multiple content categories. 40-44. (canceled)