Systems and methods for customized filtering and analysis of social media content collected over social networks

• US 20130297581A1
• Filed: 03/29/2013
• Published: 11/07/2013
• Est. Priority Date: 12/01/2009
• Status: Abandoned Application

• Current Assignee: Apple Inc.
• Original Assignee: Topsy Labs, Inc (Apple Inc.)
• Inventors: Ghosh, Rishab Aiyer, Manley, Scott Park
• Application Number:
  US13/853,741
• Publication Number:
  US 20130297581A1
• Time in Patent Office: Days
• US Class Current: 707/706
• CPC Class Codes: G06F 16/313 Selection or weighting of terms for indexing
• CPC Class Codes: G06F 16/337 Profile generation, learning or modification
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9536 Search customisation based on social or collaborative filtering

Abstract

A new approach is proposed that contemplates systems and methods to filter and/or rank a plurality of content items retrieved from a social network based on the sentiments expressed by the authors of the content items and/or the influence level of the authors over the social network. First, content items matching a set of keywords submitted by a user are retrieved from the social network. The sentiments and/or the influence levels of the authors of these content items are then identified in real time. Once identified, the sentiments and/or influence levels of the authors are used to filter and/or rank the retrieved content items to generate a search result that matches with the sentiment and/or influence level specified by the user. Finally, the customized search result based on the sentiments and/or the influence levels of the authors is presented to the user.

Claims

1. A system, comprising:

a social media content collection engine, which in operation,

accepts one or more query terms submitted by a user for search of social media content over a social network;

retrieves a plurality of content items containing all or at least a subset of the query terms from the social network in real time, wherein each of the content items is an expression of an opinion by an author;

identifies sentiment expressed by the author of each of the plurality of content items retrieved toward a specific event or topic;

filters the plurality of content items to a subset of the content items based on whether the identified sentiments of the content items are positive, neutral, or negative;

a social media content analysis engine, which in operation,

presents the content items to the user;

computes aggregate metrics or analysis of the subset of filtered content items and presents these as result to the user.

2. The system of claim 1, wherein:

the social network is a publicly accessible web-based platform or community that enables its users/members to post, share, communicate, and interact with each other.

3. The system of claim 1, wherein:

the social network is one of any other web-based communities.

4. The system of claim 1, wherein:

the content items on the social media network include one or more of citations, tweets, replies and/or re-tweets to the tweets, posts, comments to other users'"'"' posts, opinions, feeds, connections, references, links to other websites or applications, or any other activities on the social network.

5. The system of claim 1, wherein:

the social media content collection engine continuously retrieves social media content items from the social network in real time.

6. The system of claim 1, wherein:

social media content collection engine identifies the sentiment expressed by the author of a content item by analyzing the posted English text of the content item.

7. The system of claim 1, wherein:

social media content collection engine utilizes a curated sentiment dictionary of sentiment-weighted words and phrases to fine tune the sentiment detection for the content items retrieved from the specific social network.

8. The system of claim 7, wherein:

social media content collection engine applies stemming and lemmatization to expand scope of the sentiment dictionary.

9. The system of claim 1, wherein:

social media content collection engine identifies and ignores entities in the content items with misleading names for sentiment detection.

10. The system of claim 1, wherein:

social media content collection engine takes into consideration the ways people express themselves over the specific social network by identifying specific characteristics of sentiment expressions in the retrieved content items that are not only indicative of how people feel about the specific event or topic, but are also unique to how people express themselves on the social network using the content items.

11. The system of claim 1, wherein:

social media content collection engine generates the search result by matching the identified sentiments of the authors of the content items with the sentiment specified by the user.

12. The system of claim 1, wherein:

social media content collection engine ranks the search result based on the identified sentiments of the authors of the content items in the search result.

13. The system of claim 1, wherein:

social media content collection engine filters the content items based on originating locations of the content items.

14. The system of claim 1, wherein:

social media content collection engine filters the content items by language based on various language detection and processing techniques.

15. The system of claim 1, wherein:

social media content collection engine generates the search result in any language regardless of character set.

16. The system of claim 1, wherein:

social media content collection engine generates the search result by matching the identified influence level of the authors of the content items with the influence level specified by the user.

17. A system, comprising:

a social media content collection engine, which in operation,

accepts one or more query terms submitted by a user for analysis of social media content over a social network;

retrieves a plurality of content items containing all or at least a subset of the keywords from the social network in real time, wherein each of the content items is an expression of an opinion by an author;

identifies influence level of the author of each of the plurality of content items retrieved;

filters the plurality of content items to a subset of the content items based on the identified influence levels of the authors;

a social media content analysis engine, which in operation,

presents the content items to the user

computes aggregate metrics or analysis of the subset of filtered content items and presents these as result to the user.

18. The system of claim 17, wherein:

social media content collection engine calculates the influence level of an author transitively by setting the author'"'"'s influence level is higher if he/she receives attention from other people with influence than if the authors receives attention from people without influence.

19. The system of claim 17, wherein:

social media content collection engine adopts iterative influence calculation to handle circularity of the influence level by measuring centrality of an attention diagram.

20. A method, comprising:

accepting one or more query terms submitted by a user for search of social media content over a social network;

retrieving a plurality of content items containing all or at least a subset of the query terms from the social network in real time, wherein each of the content items is an expression of an opinion by an author;

identifying sentiment expressed by the author of each of the plurality of content items retrieved toward a specific event or topic;

filtering the plurality of content items to a subset of the content items based on whether the identified sentiments of the content items are positive, neutral, or negative;

presenting the subset of filtered content items as search result to the user.

computing aggregate metrics or analysis of the subset of filtered content items and presenting these as result to the user.

21. The method of claim 20, further comprising:

retrieving the social media content items continuously from the social network in real time.

22. The method of claim 20, further comprising:

identifying the sentiment expressed by the author of a content item by analyzing the posted text of the content item.

23. The method of claim 20, further comprising:

utilizing a curated sentiment dictionary of sentiment-weighted words and phrases to fine tune the sentiment detection for the content items retrieved from the specific social network.

24. The method of claim 23, further comprising:

applying stemming and lemmatization to expand scope of the sentiment dictionary.

25. The method of claim 20, further comprising:

identifying and ignoring entities in the content items with misleading names for sentiment detection.

26. The method of claim 20, further comprising:

taking into consideration the ways people express themselves over the specific social network by identifying specific characteristics of sentiment expressions in the retrieved content items that are not only indicative of how people feel about the specific event or topic, but are also unique to how people express themselves on the social network using the content items.

27. The method of claim 20, further comprising:

generating the search result by matching the identified sentiments of the authors of the content items with the sentiment specified by the user.

28. The method of claim 20, further comprising:

ranking the search result based on the identified sentiments of the authors of the content items in the search result.

29. The method of claim 20, further comprising:

filtering the content items based on originating locations of the content items.

30. The method of claim 20, further comprising:

filtering the content items by language based on various language detection and processing techniques.

31. The method of claim 20, further comprising:

generating the search result in any language regardless of character set.

32. A method, comprising:

accepting one or more keywords submitted by a user for search of social media content over a social network;

retrieving a plurality of content items containing all or at least a subset of the keywords from the social network in real time, wherein each of the content items is an expression of an opinion by an author;

identifying influence level of the author of each of the plurality of content items retrieved;

filtering the plurality of content items to a subset of the content items based on the identified influence levels of the authors;

presenting the subset of filtered content items as search result to the user.

33. The method of claim 32, further comprising:

calculating the influence level of an author transitively by setting the author'"'"'s influence level is higher if he/she receives attention from other people with influence than if the authors receives attention from people without influence.

34. The method of claim 32, further comprising:

adopting iterative influence calculation to handle circularity of the influence level by measuring centrality of an attention diagram.

35. The method of claim 32, further comprising:

social media content analysis engine generates the search result by matching the identified influence level of the authors of the content items with the influence level specified by the user.