Abstract
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.
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© 2013 Springer-Verlag Berlin Heidelberg
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Du, J., Xie, W., Li, C., Zhu, F., Lim, EP. (2013). TwiCube: A Real-Time Twitter Off-Line Community Analysis Tool. In: Meng, W., Feng, L., Bressan, S., Winiwarter, W., Song, W. (eds) Database Systems for Advanced Applications. DASFAA 2013. Lecture Notes in Computer Science, vol 7826. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37450-0_36
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DOI: https://doi.org/10.1007/978-3-642-37450-0_36
Publisher Name: Springer, Berlin, Heidelberg
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