MODELING SOCIAL NETWORKS USING ANALYTIC MEASUREMENTS OF ONLINE SOCIAL MEDIA CONTENT

• US 20100121849A1
• Filed: 01/13/2009
• Published: 05/13/2010
• Est. Priority Date: 11/13/2008
• Status: Active Grant

• Current Assignee: Buzzient, Inc.
• Original Assignee: Buzzient, Inc.
• Inventors: Goeldi, Andreas
• Granted Patent: US 8,375,024 B2
• Time in Patent Office: Days
• US Class Current: 707/736
• CPC Class Codes: G06Q 10/00 Administration; Management
• CPC Class Codes: G06Q 30/00 Commerce
• CPC Class Codes: G06Q 30/0251 Targeted advertisements
• CPC Class Codes: G06Q 30/0263 based upon Internet or website rating
• CPC Class Codes: G06Q 30/0277 Online advertisement
• CPC Class Codes: G06Q 50/01 Social networking

Abstract

Methods, apparatuses, and computer-readable media for generating a social network graph to model one or more social networks of related authors of online social media and their corresponding posts of online social media conversations relevant to subject matter of interest in a category. Embodiments are configured to harvest and aggregate posts of online social media conversations from one or more online social media sources; to perform content scraping on the posts of online social media conversations to obtain raw data that includes user-profile information of a social media author corresponding to each individual post of online social media conversations; and performing social network analysis processing on the raw data to obtain the social network graph.

Claims

1. A method comprising:

generating a social network graph to model one or more social networks of related authors of online social media and their corresponding posts of online social media conversations relevant to subject matter of interest in a category, wherein generating the social network graph comprises;

harvesting and aggregating posts of online social media conversations from one or more online social media sources;

performing content scraping on the posts of online social media conversations to obtain raw data including each individual post of an online social media conversation relevant to the subject matter of interest and user-profile information of a social media author corresponding to each individual post; and

performing social network analysis processing on the raw data to obtain the social network graph.

2. The method of claim 1, further comprising storing the social network graph in a database.

3. The method of claim 1, wherein harvesting the online social media conversations includes:

performing forum analysis to discover websites of interest containing online social media content relevant to the subject matter of interest in the category; and

searching through the websites of interest to extract social media conversations related to the subject matter of interest.

4. The method of claim 3, wherein the forum analysis comprises:

searching for websites with online social media content relevant to the subject matter of interest using keywords in a search engine;

assigning a relevance score to each website found in search engine results based on the keywords; and

designating websites with a high relevance score as websites of interest.

5. The method of claim 1, wherein the content scraping comprises:

identifying hyperlinks to potentially relevant online social media conversations in one or more web pages of each of the websites of interest;

iteratively accessing and retrieving multiple levels of web pages within the each of the websites of interest using the hyperlinks until relevant conversation threads are found;

breaking down each relevant conversation thread into individual posts of online social media conversations; and

storing the raw data in the database.

6. The method of claim 5, wherein the raw data further comprises information on those social media authors responding to each of the individual posts.

7. The method of claim 1, wherein the user-profile information of the social media authors includes one or more of:

author'"'"'s username;

author'"'"'s demographic and geographic information;

number of conversations the author has posted to the website; and

online social media connections of the author.

8. The method of claim 1, wherein the social network analysis processing comprises:

determining influence of each of the authors within the one or more social networks of related authors of online social media and their corresponding posts;

ranking the influence of each of the authors to ascertain most influential authors for the category; and

compiling a list of the most influential authors for the category sorted by influence.

9. The method of claim 8, wherein the influence of each of the online social media authors is determined by:

calculating a centrality value for each author using a betweenness centrality algorithm on the raw data stored in the database for each of the websites of interest, the centrality value to indicate a degree of influence of the author in the one or more social networks; and

calculating an influence score for each author based on the centrality value of the author to determine the influence of each of the authors within the one or more social networks of related authors of online social media and their corresponding posts.

10. The method of claim 9, wherein the influence score for each of the authors is further based on a number of active authors on the websites of interest and number of posts to the websites of interest by each author.

11. The method of claim 9, further comprising modifying the centrality value by an activity level of each of the authors and by an importance of the website where the author is active.

12. A method for enhancing customer service at a call center comprising:

receiving a customer service call at the call center from a customer concerning a product or service;

retrieving quantitative structured actionable information about the customer contained in a social network graph stored in a database, the social network graph to model one or more social networks of related authors online social media and their corresponding posts of online social media conversations; and

providing enhanced customer service at the call center based on the actionable information.

13. The method of claim 12, further comprising one or more of:

recommending or performing an action based on the actionable information about the customer; and

providing guidance to a call-center operator on how to respond to the customer service call based on the actionable information.

14. A method of gathering enhanced national defense intelligence comprising:

retrieving quantitative structured actionable information relating to potential perpetrators of violent terrorist activity contained in a social network graph stored in a database, the social network graph to model one or more social networks of related authors online social media and their corresponding posts of online social media conversations; and

identifying the potential perpetrators of violent terrorist activity in posts of unstructured qualitative online social media conversations based on the actionable information.

15. The method of claim 14, further comprising identifying online social media participants as potentially affiliated with one or more groups known to engage in the violent terrorist activity based on analyzing the actionable information contained in the social network graph.

16. The method of claim 15, further comprising determining whether certain online social media participants are affiliated with authors previously identified as affiliated with one or more groups known to engage in violent terrorist activity based on the social network graph.

17. The method of claim 16, further comprising identifying previously unknown online social media sources used by groups to engage in violent terrorist activity based on connections between authors of online social media previously identified as affiliated with one or more groups known to engage in violent terrorist activity and their corresponding posts to the previously unknown online social media sources used by these groups.

18. The method of claim 17, further comprising identifying influential online social media authors previously identified as affiliated with one or more groups known to engage in violent terrorist activity based on connections between authors online social media represented in the one or more social networks modeled by the social network graph.

19. The method of claim 18, further comprising ranking the influential authors of online social media by influence to generate further actionable information on complex social networks of persons and groups known to engage in violent terrorist activity.

20. An article of manufacture comprising:

a computer-readable storage medium providing instructions which, when executed by a computer, cause the computer to perform a method, the instructions comprising;

instructions to generate a social network graph to model one or more social networks of related authors of online social media and their corresponding posts of online social media conversations relevant to subject matter of interest in a category, wherein the instructions to generate the social network graph comprise;

instructions to harvest and aggregate posts of online social media conversations from one or more online social media sources;

instructions to perform content scraping on the posts of online social media conversations to obtain raw data including each individual post of an online social media conversation relevant to the subject matter of interest and user-profile information of a social media author corresponding to each individual post; and

instructions to perform social network analysis processing on the raw data to obtain the social network graph.

21. The article of manufacture of claim 20, further comprising instructions to store the social network graph in a database.

22. The article of manufacture of claim 20, wherein the instructions to harvest the online social media conversations include:

instructions to perform forum analysis to discover websites of interest containing online social media conversations relevant to the subject matter of interest; and

instructions to search through the websites of interest to extract the social media conversations related to the subject matter of interest.

23. The article of manufacture of claim 21, wherein the forum analysis comprises:

instructions to search for websites with online social media conversations relevant to the subject matter of interest using keywords in a search engine;

instructions to assign a relevance score to each website found in search engine results based on the keywords; and

instructions to designate websites with a high relevance score as websites of interest.

24. The article of manufacture of claim 20, wherein the content scraping comprises:

instructions to identify hyperlinks to potentially relevant online social media conversations in one or more web pages of the website of interest;

instructions to iteratively access and retrieve multiple levels of web pages within the website of interest using the hyperlinks in the one or more web pages until relevant conversation threads are found;

instructions to break down each relevant conversation thread into individual posts of online social media conversations; and

instructions to store the raw data in the database.

25. The article of manufacture of claim 24, wherein the raw data further comprises information on those social media authors responding to each of the individual posts.

26. The article of manufacture of claim 20, wherein the instructions to perform social network analysis processing comprise:

instructions to determine influence of the each of the authors within the one or more social networks of related authors of online social media and their corresponding posts;

instructions to rank the influence of each of the authors to ascertain most influential authors for the category; and

instructions to compile a list of the most influential authors for the category sorted by influence.

27. The article of manufacture of claim 26, wherein the influence of each of the online social media authors is determined by:

instructions to calculate a centrality value for each author using a betweenness centrality algorithm on the raw data stored in the database for each of the websites of interest, the centrality value to indicate a degree of influence of the author in the one or more social networks; and

instructions to calculate and influence score for each author based on the centrality value of the author to determine the influence of each of the authors within the one or more social networks of related authors of online social media and their corresponding posts.

28. An article of manufacture comprising:

a computer-readable storage medium providing instructions which, when executed by a computer, cause the computer to perform a method for enhancing customer service at a call center, the instructions comprising;

instructions to receive a customer service call at the call center from a customer concerning a product or service;

instructions to retrieve quantitative structured actionable information about the customer contained in a social network graph stored in a database, the social network graph to model one or more social networks of related authors online social media and their corresponding posts of online social media conversations; and

instructions to provide enhanced customer service at the call center based on the actionable information.

29. The article of manufacture of claim 28, further comprising instructions to take action based on the actionable information about the customer including one or more of:

instructions to recommend or perform an action based on the actionable information about the customer; and

instructions to provide guidance to a call-center operator on how to respond to the customer service call based on the actionable information.

30. The article of manufacture of claim 29, further comprising instructions to identify influential authors of online social media based on the actionable information about the customer so that a call-center operator can actively engage influential authors.

31. An article of manufacture comprising:

a computer-readable storage medium providing instructions which, when executed by a computer, cause the computer to perform a method of gathering enhanced national defense intelligence, the instructions comprising;

instructions to retrieve quantitative structured actionable information relating to potential perpetrators of violent terrorist activity contained in a social network graph stored in a database, the social network graph to model one or more social networks of related authors online social media and their corresponding posts of online social media conversations; and

instructions to identify potential perpetrators of violent terrorist activity in posts of unstructured qualitative online social media conversations based on the actionable information.

32. The article of manufacture of claim 31, further comprising instructions to identify online social media participants as potentially affiliated with one or more groups known to engage in the violent terrorist activity based on analyzing the actionable information contained in the social network graph.

33. The article of manufacture of claim 32, further comprising instructions to determine whether certain online social media participants are affiliated with authors previously identified as affiliated with one or more groups known to engage in violent terrorist activity based on the social network graph.

34. The article of manufacture of claim 33, further comprising instructions to identify previously unknown online social media sources used by groups to engage in violent terrorist activity based on connections between authors of online social media previously identified as affiliated with one or more groups known to engage in violent terrorist activity and their corresponding posts to the previously unknown online social media sources used by these groups.

35. The article of manufacture of claim 34, further comprising instructions to identify influential online social media authors previously identified as affiliated with one or more groups known to engage in violent terrorist activity based on connections between authors online social media represented in the one or more social networks modeled by the social network graph.

36. The article of manufacture of claim 35, further comprising instructions to rank the influential authors of online social media by influence to generate further actionable information on complex social networks of persons and groups known to engage in violent terrorist activity.

37. An apparatus comprising:

a harvesting module to discover and collect online social media conversations relevant to a subject matter of interest in a category from one or more online social media sources; and

a content scraping module to process the posts of online social media conversations to obtain raw data including each individual post of an online social media conversation relevant to the subject matter of interest and user-profile information of a social media author corresponding to each individual post; and

a processing module to perform social network analysis processing on the raw data to obtain a social network graph, the social network graph to model one or more social networks of related authors of online social media and their corresponding posts of online social media conversations relevant to the subject matter of interest.

38. The apparatus of claim 37, wherein the harvesting module comprises:

a forum analyzer to discover websites of interest containing online social media content relevant to the subject matter of interest; and

a database to store the raw data.

39. The apparatus of claim 38, wherein the raw data further comprises information on those social media authors responding to each of the individual posts.

40. The apparatus of claim 39, wherein the processing module is configured to:

process the raw data stored in the database to determine influence of each of the authors within the one or more social networks of related authors of online social media and their corresponding posts;

rank the influence of each of the authors to ascertain most influential authors in the category; and

compile a list of the most influential authors for the category sorted by influence.