METHOD AND SYSTEM FOR PERFORMING TREND ANALYSIS OF THEMES IN SOCIAL DATA

• US 20140278769A1
• Filed: 03/12/2013
• Published: 09/18/2014
• Est. Priority Date: 03/12/2013
• Status: Active Grant

• Current Assignee: Oracle International Corporation (Oracle Corporation)
• Original Assignee: Oracle International Corporation (Oracle Corporation)
• Inventors: MCCANDLESS, Timothy P., SETAYESH, Mehrshad
• Granted Patent: US 10,909,550 B2
• Time in Patent Office: Days
• US Class Current: 705/7.31
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data

Abstract

Disclosed is an improved method, system, and computer program product for performing trend analysis of themes from social media data. Semantic analysis is performed on content that appear on social media sites. The results of the semantic analysis can be used to identify themes within the social media data over a period of time. Trend analysis is performed over the identified themes. An enterprise or business can more effectively market to the consumers based upon this knowledge of the consumers'"'"' interests.

Claims

1. A computer implemented method for analyzing social media data, comprising:

receiving social media data from one or more social media sources;

performing semantic analysis upon the social media data over a timeframe;

generating a trend analysis for the social media data for a topic of interest to a business enterprise; and

generating actionable data that can be acted upon by the business enterprise to address the trend analysis data.

2. The method of claim 1, wherein the trend analysis data comprises theme analysis corresponding to consumer interest over the timeframe.

3. The method of claim 1, wherein the trend analysis comprises sentiment analysis for the topic over the timeframe.

4. The method of claim 3, in which the trend analysis further comprises theme analysis for the topic, and sentiment analysis and the theme analysis are reviewed in conjunction with each other.

5. The method of claim 1, in which the semantic analysis comprises latent semantic analysis that analyzes contextual and semantic significance of terms that appear within the social media data.

6. The method of claim 1, wherein semantic filtering is performed to reduce irrelevant data.

7. The method of claim 1, wherein the actionable data is supplied to an enterprise software system.

8. The method of claim 7, wherein the enterprise software system comprises at least one of a customer relations management (“

CRM”

) application, enterprise resource planning (“

ERP”

) application, and supply chain management application.

9. A computer program product embodied on a computer usable medium, the computer readable medium having stored thereon a sequence of instructions which, when executed by a processor causes the processor to execute a method for analyzing social media data, the method comprising:

receiving social media data from one or more social media sources;

performing semantic analysis upon the social media data over a timeframe;

generating a trend analysis for the social media data for a topic of interest to a business enterprise; and

generating actionable data that can be acted upon by the business enterprise to address the trend analysis data.

10. The computer program product of claim 9, wherein the trend analysis data comprises theme analysis corresponding to consumer interest over the timeframe.

11. The computer program product of claim 9, wherein the trend analysis comprises sentiment analysis for the topic over the timeframe.

12. The computer program product of claim 11, in which the trend analysis further comprises theme analysis for the topic, and sentiment analysis and the theme analysis are reviewed in conjunction with each other.

13. The computer program product of claim 9, in which the semantic analysis comprises latent semantic analysis that analyzes contextual and semantic significance of terms that appear within the social media data.

14. The computer program product of claim 9, wherein semantic filtering is performed to reduce irrelevant data.

15. The computer program product of claim 9, wherein the actionable data is supplied to an enterprise software system.

16. The computer program product of claim 15, wherein the enterprise software system comprises at least one of a customer relations management (“

CRM”

) application, enterprise resource planning (“

ERP”

) application, and supply chain management application.

17. A computer system for analyzing social media data, comprising:

a computer processor to execute a set of program code instructions; and

a memory to hold the program code instructions, in which the program code instructions comprises program code to perform, wherein the program code instructions comprises instructions for receiving social media data from one or more social media sources, performing semantic analysis upon the social media data over a timeframe, generating a trend analysis for the social media data for a topic of interest to a business enterprise, and generating actionable data that can be acted upon by the business enterprise to address the trend analysis data.

18. The system of claim 17, wherein the trend analysis data comprises theme analysis corresponding to consumer interest over the timeframe.

19. The system of claim 17, wherein the trend analysis comprises sentiment analysis for the topic over the timeframe.

20. The system of claim 19, in which the trend analysis further comprises theme analysis for the topic, and sentiment analysis and the theme analysis are reviewed in conjunction with each other.

21. The system of claim 17, in which the semantic analysis comprises latent semantic analysis that analyzes contextual and semantic significance of terms that appear within the social media data.

22. The system of claim 17, wherein semantic filtering is performed to reduce irrelevant data.

23. The system of claim 17, wherein the actionable data is supplied to an enterprise software system.

24. The system of claim 23, wherein the enterprise software system comprises at least one of a customer relations management (“

CRM”

) application, enterprise resource planning (“

ERP”

) application, and supply chain management application.