Comparing the pulses of categorical hot events in Twitter and Weibo

The fragility and interconnectivity of the planet argue compellingly for a greater understanding of how different communities make sense of their world. One of such critical demands relies on comparing the Chinese and the rest of the world (e.g., Americans), where communities' ideological and cultural backgrounds can be significantly different. While traditional studies aim to learn the similarities and differences between these communities via high-cost user studies, in this paper we propose a much more efficient method to compare different communities by utilizing social media. Specifically, Weibo and Twitter, the two largest microblogging systems, are employed to represent the target communities, i.e. China and the Western world (mainly United States), respectively. Meanwhile, through the analysis of the Wikipedia page-click log, we identify a set of categorical `hot events' for one month in 2012 and search those hot events in Weibo and Twitter corpora along with timestamps via information retrieval methods. We further quantitatively and qualitatively compare users' responses to those events in Twitter and Weibo in terms of three aspects: popularity, temporal dynamic, and information diffusion. The comparative results show that although the popularity ranking of those events are very similar, the patterns of temporal dynamics and information diffusion can be quite different.

[1]  Jon Kleinberg,et al.  Differences in the mechanics of information diffusion across topics: idioms, political hashtags, and complex contagion on twitter , 2011, WWW.

[2]  Dennis M. Murphy The Net Delusion: The Dark Side of Internet Freedom , 2012 .

[3]  Johan Bollen,et al.  Modeling Public Mood and Emotion: Twitter Sentiment and Socio-Economic Phenomena , 2009, ICWSM.

[4]  Bin Zhao,et al.  Discovering Collective Viewpoints on Micro-blogging Events Based on Community and Temporal Aspects , 2011, ADMA.

[5]  Evgeny V. Morozov,et al.  Response to Philip N. Howard's review of The Net Delusion: The Dark Side of Internet Freedom , 2011, Perspectives on Politics.

[6]  Jie Tang,et al.  What is the Nature of Chinese MicroBlogging: Unveiling the Unique Features of Tencent Weibo , 2012, 1211.2197.

[7]  Xiaozhong Liu,et al.  Mirroring the real world in social media: twitter, geolocation, and sentiment analysis , 2013, UnstructureNLP@CIKM.

[8]  Xiaozhong Liu,et al.  Computational community interest for ranking , 2009, CIKM.

[9]  Fareed Zakaria,et al.  The Post-American World: Release 2.0 , 2011 .

[10]  Hosung Park,et al.  What is Twitter, a social network or a news media? , 2010, WWW '10.

[11]  Johan Bollen,et al.  Improving news ranking by community tweets , 2012, WWW.

[12]  Yutaka Matsuo,et al.  Earthquake shakes Twitter users: real-time event detection by social sensors , 2010, WWW '10.

[13]  M. Osborne,et al.  Using Prediction Markets and Twitter to Predict a Swine Flu Pandemic , 2009 .

[14]  Robert E. Pinsker,et al.  Alone Together: Why We Expect More from Technology and Less from Each Other. , 2012 .

[15]  Bernard J. Jansen,et al.  Twitter power: Tweets as electronic word of mouth , 2009, J. Assoc. Inf. Sci. Technol..

[16]  Rizal Setya Perdana What is Twitter , 2013 .

[17]  Patrick Paroubek,et al.  Twitter as a Corpus for Sentiment Analysis and Opinion Mining , 2010, LREC.

[18]  Yong Yu,et al.  A comparative study of users' microblogging behavior on sina weibo and twitter , 2012, UMAP.

[19]  Kerk F. Kee,et al.  Is There Social Capital in a Social Network Site?: Facebook Use and College Students’ Life Satisfaction, Trust, and Participation 1 , 2009 .

[20]  Peggy M. Dillon Alone Together: Why We Expect More from Technology and Less from Each Other , 2011 .

[21]  Fareed Zakaria,et al.  The Post-American World , 2008 .

[22]  Zhigang Cao,et al.  Analyzing user behavior of the micro-blogging website Sina Weibo during hot social events , 2013, 1304.3898.

[23]  Xiaozhong Liu,et al.  Real-time user interest modeling for real-time ranking , 2013, J. Assoc. Inf. Sci. Technol..

[24]  Jure Leskovec,et al.  Information diffusion and external influence in networks , 2012, KDD.

[25]  Gerhard Weikum,et al.  Integrating DB and IR Technologies: What is the Sound of One Hand Clapping? , 2005, CIDR.

[26]  Timothy W. Finin,et al.  Why we twitter: understanding microblogging usage and communities , 2007, WebKDD/SNA-KDD '07.