1. Delft University of Technology A Comparative Study of Users’ Microblogging Behavior on Sina Weibo and Twitter Qi Gao Web Information Systems Delft University of Technology

2. 2 Microblogging Behavior on Sina Weibo and Twitter What we study: microblogging behavior Wikipedia:Twitter Wikipedia:Sina_Weibo 340,000,000 500,000,000 100,000,000 250,000,000 What are the differences in Chinese and Western users’ microblogging behavior?

3. 3 Microblogging Behavior on Sina Weibo and Twitter Cultural differences acting as a member of a groupstanding up for himself Flickr:webeiFlickr:semicharmed

4. 4 Microblogging Behavior on Sina Weibo and Twitter Data sources follower/followee network limited length of a post repost/reply/like use of URLs and hashtags meta information (time, source)

5. 5 Microblogging Behavior on Sina Weibo and Twitter User modeling and analysis framework Microblogging Platforms Semantic Web Cultural Analytics syntactic analysis temporal analysis semantic analysis sentiment analysis Data Processing and User Profiling topic/interest modeling semantic enrichment data acquisition metadata extraction user profile construction multilingual NER

6. 6 Microblogging Behavior on Sina Weibo and Twitter User profiling Profile ? What could go wrong? RT @DRUGE_REPORT Washington: White House seeks ‘Control’ over communication during ‘crisis’ #obama drudge.tw/LVZygj

7. 7 Microblogging Behavior on Sina Weibo and Twitter User profiling – syntactic characteristics Profile hashtag/URL # What could go wrong? RT @DRUGE_REPORT Washington: White House seeks ‘Control’ over communication during ‘crisis’ #obama drudge.tw/LVZygj

8. 8 Microblogging Behavior on Sina Weibo and Twitter User profiling – semantic characteristics Profile hashtag/URL # entity What could go wrong? RT @DRUGE_REPORT Washington: White House seeks ‘Control’ over communication during ‘crisis’ #obama drudge.tw/LVZygj

9. 9 Microblogging Behavior on Sina Weibo and Twitter User profiling – semantic characteristics Profile hashtag/URL # entity T topic What could go wrong? RT @DRUGE_REPORT Washington: White House seeks ‘Control’ over communication during ‘crisis’ #obama drudge.tw/LVZygj topic:organization topic:person topic:location

10. 10 Microblogging Behavior on Sina Weibo and Twitter User profiling – sentiment characteristics Profile hashtag/URL # entity T topic What could go wrong? RT @DRUGE_REPORT Washington: White House seeks ‘Control’ over communication during ‘crisis’ #obama drudge.tw/LVZygj sentiment neutral positive negative

11. 11 Microblogging Behavior on Sina Weibo and Twitter User profiling – temporal characteristics Profile hashtag/URL # entity T topic What could go wrong? RT @DRUGE_REPORT Washington: White House seeks ‘Control’ over communication during ‘crisis’ #obama drudge.tw/LVZygj sentiment temporal information

12. 12 Microblogging Behavior on Sina Weibo and Twitter Analysis of users’ microblogging behavior Datasets Microblog data collected from Sina Weibo and Twitter over a period of three months > 46 million micropost overall – 22m from Sina Weibo and 24m from Twitter a sample of 2616 Sina Weibo users and 1200 Twitter users Analyze and compare user behavior on Sina Weibo and Twitter on two levels (i) the entire user population and (ii) individual users from different angles (i) syntactic, (ii) semantic, (iii) sentiment and (iv) temporal analysis relate our findings to theories about cultural stereotypes (Hofstede’s cultural dimensions)

13. 13 Microblogging Behavior on Sina Weibo and Twitter Cultural model: Hofstede’s cultural dimensions Describes stereotypical cultural characteristics of nationalities Five core dimensions: Power Distance (PDI) Individualism versus Collectivism (IDV) Masculinity versus Femininity (MAS) Uncertainty Avoidance (UAI) Long-Term Orientation (LTO) Scores are relative wrt. other nationalities geert-hofstede.com

14. 14 Microblogging Behavior on Sina Weibo and Twitter Hashtags and URLs are less frequently applied on Sina Weibo than on Twitter. Users on Twitter are more triggered by hashtags and URLs when propagating information than on Sina Weibo. hashtag-Weibo hashtag-Twitter URL-Twitter URL-Weibo Syntactic analysis – what are the syntactical characteristics of messages?

15. 15 Microblogging Behavior on Sina Weibo and Twitter Hashtags and URLs are less frequently applied on Sina Weibo than on Twitter. Users on Twitter are more triggered by hashtags and URLs when propagating information than on Sina Weibo. Syntactic analysis – what are the syntactical characteristics of messages? Cultural Differences high collectivism (Sina Weibo) high individualism (Twitter)

16. 16 Microblogging Behavior on Sina Weibo and Twitter Semantic analysis – what kind of topics are discussed? The topics that users discuss on Sina Weibo are to a large extent related to locations and persons. In contrast to Sina Weibo, users on Twitter are talking more about organizations (such as companies, political parties). Weibo Twitter

17. 17 Microblogging Behavior on Sina Weibo and Twitter Semantic analysis – what kind of topics are discussed? The topics that users discuss on Sina Weibo are to a large extent related to locations and persons. In contrast to Sina Weibo, users on Twitter are talking more about organizations (such as companies, political parties). Cultural Differences high collectivism (Sina Weibo) high individualism (Twitter)

18. 18 Microblogging Behavior on Sina Weibo and Twitter Sentiment analysis – what are the sentiment characteristics of microposts? Sina Weibo users have a stronger tendency to publish positive messages than Twitter users. Weibo Twitter

19. 19 Microblogging Behavior on Sina Weibo and Twitter Combining semantic and sentiment analysis The difference is amplified when discussing ‘people’ or ‘location’, with Sina Weibo users even more positive and Twitter users more negative.

20. 20 Microblogging Behavior on Sina Weibo and Twitter Combining semantic and sentiment analysis The difference is amplified when discussing ‘people’ or ‘location’, with Sina Weibo users even more positive and Twitter users more negative. Cultural Differences long-term orientation (Sina Weibo) short-tem orientation (Twitter)

21. 21 Microblogging Behavior on Sina Weibo and Twitter Temporal analysis – how quickly do users propagate information? Twitter users repost messages faster than Sina Weibo users. time distance = t repost - t original post Weibo Twitter

22. 22 Microblogging Behavior on Sina Weibo and Twitter Temporal analysis – how quickly do users propagate information? Twitter users repost messages faster than Sina Weibo users. Cultural Differences large degree of power distance (Sina Weibo) low degree of power distance (Twitter)

23. 23 Microblogging Behavior on Sina Weibo and Twitter Qi Gao et al. Information Propagation Cultures on Sina Weibo and Twitter. In Proceedings of ACM Web Science Conference 2012. Evanston, USA.

24. 24 Microblogging Behavior on Sina Weibo and Twitter Conclusion and future work What we did user modeling framework for culture-aware user modeling based on microblogging data data-intensive analyses deliver valuable insights for multilingual and culture- aware user modeling Findings key differences between Chinese and US/Western users’ microblogging behavior – e.g. Chinese microblogging activities are more positive and less ‘political’ some of the differences can be explained with cultural model from social science research – e.g. Hofstede: individualism vs. collectivism Future work: develop personalized applications that are able to adapt to the cultural factors

25. 25 Microblogging Behavior on Sina Weibo and Twitter q.gao@tudelft.nl @wisdelft Thank You! Q & A Qi Gao, Fabian Abel, Geert-Jan Houben, Yong Yu