Conference Proceeding Article
As a micro-blogging service, Twitter differs from other social network services in two ways: 1) the absence of mutual consent in establishing follow links and 2) being a mixture of news media and social network. A key question to ask in better understanding Twitter user behavior is which part of a user’s Twitter network reflects one’s real-life social network. TwiCube is an online tool that employs a novel algorithm capable of identifying a user’s real-life social community, which we call the user’s off-line community, purely from examining the link structure among the user’s followers and followees. Based on the identified off-line community, TwiCube provides a summary of the user’s interests, tweeting habits and neighborhood popularity analysis. Evaluations from real Twitter users demonstrate that our off-line community detection approach achieves high precision and recall in most cases.
Communication Technology and New Media | Databases and Information Systems
Data Management and Analytics
Database Systems for Advanced Applications: 18th International Conference, DASFAA 2013, Wuhan, China, April 22-25, 2013. Proceedings, Part II
City or Country
DU, Juan; XIE, Wei; LI, Cheng; ZHU, Feida; and LIM, Ee Peng.
TwiCube: A Real-time Twitter Online Community Analysis Tool. (2013). Database Systems for Advanced Applications: 18th International Conference, DASFAA 2013, Wuhan, China, April 22-25, 2013. Proceedings, Part II. 7826, (2), 458-462. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/1732