DocumentCode
3082013
Title
Topical Evolution and Regional Affinity of Tweets
Author
Dey, Lipika ; Khurdiya, Arpit ; Mahajan, Dhruv
Author_Institution
Innovation Labs., Delhi Tata Consultancy Services, Gurgaon, India
fYear
2013
fDate
24-26 Aug. 2013
Firstpage
297
Lastpage
300
Abstract
Business organizations are increasingly showing interest in Twitter content to know their consumers. Tracking popular tags and trends give some idea about what people are talking about. However, in order to act on the knowledge acquired, they need more detailed information like regional variability in content, exact location of discontent if any, regional affinities and influences etc. In this work, we present methods to identify topics of discussion in tweets using a LDA-based approach, which can identify emerging or evolving topics. Regional analysis of topics can provide interesting business insights about consumer expectation or behavioural variations. Further, regional distribution of topics are analysed to identify clusters of regions that tend to behave similarly over extended periods of time.
Keywords
business data processing; consumer behaviour; data mining; social networking (online); statistical analysis; text analysis; LDA-based approach; Twitter content; behavioural variation; business insight; business organization; consumer expectation; popular tags; regional affinity; regional variability; topic regional distribution; topical evolution; trends; tweets; Data mining; Market research; Matrix decomposition; Media; Organizational aspects; Twitter; Clustering; Regional Dispersion; Social Media Analytics; Topic extraction; regional clusters;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational and Business Intelligence (ISCBI), 2013 International Symposium on
Conference_Location
New Delhi
Print_ISBN
978-0-7695-5066-4
Type
conf
DOI
10.1109/ISCBI.2013.66
Filename
6724371
Link To Document