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Social Network Analysis and Mining

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01-12-2015 | Original Article

Topic dynamics in Weibo: a comprehensive study

Authors: Rui Fan, Jichang Zhao, Ke Xu

Published in: Social Network Analysis and Mining | Issue 1/2015

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Abstract

The tremendous development of online social media has changed people’s life fundamentally in recent years. Weibo, a Twitter-like service in China, has attracted more than 500 million users in less than 5 years and produces more than 100 million Chinese tweets everyday. In these massive tweets, different user interests and daily trends are reflected by different topics. To our best knowledge, a systematic investigation of topic dynamics in Weibo is still missing. Aiming at filling this vital gap, we try to comprehensively disclose the topic dynamics from the perspective of time, geography, demographics, emotion, retweeting and correlation. An incremental learning framework is first established to probe more than 200 million streaming tweets and an interaction network constituted by around 90,000 active users. Many interesting patterns are then revealed, which could provide insights for topic-related applications in online social media, such as user profiling, event detection, trend tracking or content recommendation.

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Title: Topic dynamics in Weibo: a comprehensive study
Authors: Rui Fan
Jichang Zhao
Ke Xu
Publication date: 01-12-2015
Publisher: Springer Vienna
Published in: Social Network Analysis and Mining / Issue 1/2015
Print ISSN: 1869-5450
Electronic ISSN: 1869-5469
DOI: https://doi.org/10.1007/s13278-015-0282-0

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