Publication Type

Conference Proceeding Article

Publication Date

6-2012

Abstract

Twitter is a fast-growing online social network service (SNS) where users can "follow" any other user to receive his or her mini-blogs which are called "tweets". In this paper, we study the problem of identifying a user's off-line real-life social community, which we call the user'sTwitter off-line community, purely from examining Twitter network structure. Based on observations from our user-verified Twitter data and results from previous works, we propose three principles about Twitter off-line communities. Incorporating these principles, we develop a novel algorithm to iteratively discover the Twitter off-line community based on a new way of measuring user closeness. According to ground truth provided by real Twitter users, our results demonstrate the effectiveness of our approach with both high precision and recall in most cases.

Discipline

Databases and Information Systems | Social Media

Publication

WebSci '12 : proceedings of the 3rd annual ACM Web Science Conference, 2012, Evanston, IL, USA

Identifier

10.1145/2380718.2380763

Publisher

ACM

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

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