A Comparative Study of Users'Microbloggin Behavior on sina weibo and twitter Qi Gao!, Fabian Abell, Geert-Jan Houben, Yong Yu2 1 Web Information Systems, Delft University of Technology 2 APEX Data Knowledge Management Lab, Shanghai Jiaotong University (agao,f.abel,g.j.p.m.houben]otudelftnl,yyu@apex.stju.edu.cn Abstract. In this article, we analyze and compare user behavior on vo different microblogging platforms:(1)Sina Weibo which is the most popular microblogging service in China and(2) Twitter. Such a com- arison has not been done before at this scale and is therefore essential for understanding user behavior on microblogging services. In our study we analyze more than 40 million microblogging activities and investigate microblogging behavior from different angles. We(i) analyze how people access microblogs and (ii) compare the writing style of Sina Weibo and Twitter users by analyzing textual features of microposts. Based on se- mantics and sentiments that our user modeling framework extracts from English and Chinese posts, we study and compare(iii)the topics and (iv) sentiment polarities of posts on Sina Weibo and Twitter. Furthermore (v) we investigate the temporal dynamics of the microblogging behavior such as the drift of user interests over time Our results reveal significant differences in the microblogging behavior on Sina Weibo and twitter and deliver valuable insights for multilingual and culture-aware user modeling based on microblogging data. We also explore the correlation between some of these differences and cultural models from social science research Key words: user modeling, microblogging, comparative usage analysis Microblogging services such as Twitter allow people to publish, share and dis- cuss short messages on the Web. Nowadays, Twitter users publish more than 200 million posts, so-called tweets, per day. In China, Sina Weibo is lead ing the microblogging market since twitter is unavailable. Both Sina Weibo and Twitter basically feature the same functionality. For example, both services limit che lengths of microposts to 140 characters and allow users to organize them- selves in a follower-followee network, where people follow the message updates of other users(unidirectional relationship). Sina Weibo and Twitter provide(real time) access to the microposts via APIs and therefore allow for investigating and analyzing interesting applications and functionality such as event detection [1 2] or recommending Web sites 3 By analyzing individual microblogging activities, it is possible to learn about the characteristics, preferences and concerns of users. In previous work, we there- http://blog.twittercom/2011/06/200-million-tweets-per-day.html http://www.weibo.comA Comparative Study of Users’ Microblogging Behavior on Sina Weibo and Twitter Qi Gao1 , Fabian Abel1 , Geert-Jan Houben1 , Yong Yu2 1 Web Information Systems, Delft University of Technology 2 APEX Data & Knowledge Management Lab, Shanghai Jiaotong University {q.gao,f.abel,g.j.p.m.houben}@tudelft.nl, yyu@apex.stju.edu.cn Abstract. In this article, we analyze and compare user behavior on two different microblogging platforms: (1) Sina Weibo which is the most popular microblogging service in China and (2) Twitter. Such a com￾parison has not been done before at this scale and is therefore essential for understanding user behavior on microblogging services. In our study, we analyze more than 40 million microblogging activities and investigate microblogging behavior from different angles. We (i) analyze how people access microblogs and (ii) compare the writing style of Sina Weibo and Twitter users by analyzing textual features of microposts. Based on se￾mantics and sentiments that our user modeling framework extracts from English and Chinese posts, we study and compare (iii) the topics and (iv) sentiment polarities of posts on Sina Weibo and Twitter. Furthermore, (v) we investigate the temporal dynamics of the microblogging behavior such as the drift of user interests over time. Our results reveal significant differences in the microblogging behavior on Sina Weibo and Twitter and deliver valuable insights for multilingual and culture-aware user modeling based on microblogging data. We also explore the correlation between some of these differences and cultural models from social science research. Key words: user modeling, microblogging, comparative usage analysis 1 Introduction Microblogging services such as Twitter allow people to publish, share and dis￾cuss short messages on the Web. Nowadays, Twitter users publish more than 200 million posts, so-called tweets, per day3 . In China, Sina Weibo4 is lead￾ing the microblogging market since Twitter is unavailable. Both Sina Weibo and Twitter basically feature the same functionality. For example, both services limit the lengths of microposts to 140 characters and allow users to organize them￾selves in a follower-followee network, where people follow the message updates of other users (unidirectional relationship). Sina Weibo and Twitter provide (real￾time) access to the microposts via APIs and therefore allow for investigating and analyzing interesting applications and functionality such as event detection [1, 2] or recommending Web sites [3]. By analyzing individual microblogging activities, it is possible to learn about the characteristics, preferences and concerns of users. In previous work, we there￾fore introduced a semantic user modeling framework for inferring user interests 3 http://blog.twitter.com/2011/06/200-million-tweets-per-day.html 4 http://www.weibo.com/