A Comparative Study of Users’ Microblogging Behavior on Sina Weibo and Twitter

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

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

3. Cultural differences standing up for himself acting as a member of a group Flickr:semicharmed Flickr:webei

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

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

6. User profiling ? Profile What could go wrong? RT @DRUGE_REPORT Washington: White House seeks ‘Control’ over communication during ‘crisis’ #obamadrudge.tw/LVZygj

7. User profiling – syntactic characteristics hashtag/URL # Profile What could go wrong? RT @DRUGE_REPORT Washington: White House seeks ‘Control’ over communication during ‘crisis’ #obamadrudge.tw/LVZygj

8. User profiling – semantic characteristics hashtag/URL # Profile What could go wrong? RT @DRUGE_REPORT Washington: White House seeks ‘Control’ over communication during ‘crisis’ #obamadrudge.tw/LVZygj entity

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

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

11. User profiling – temporal characteristics hashtag/URL # Profile What could go wrong? RT @DRUGE_REPORT Washington: White House seeks ‘Control’ over communication during ‘crisis’ #obamadrudge.tw/LVZygj entity topic T sentiment temporal information

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

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

16. Semantic analysis – what kind of topics are discussed? Weibo Twitter 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).

17. Semantic analysis – what kind of topics are discussed? Cultural Differences high collectivism (Sina Weibo) high individualism (Twitter) 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).

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

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

21. Temporal analysis – how quickly do users propagate information? Weibo time distance = trepost- toriginal post Twitter Twitter users repost messages faster than Sina Weibo users.

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

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

24. 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. Thank You! Q & A QiGao, Fabian Abel, Geert-Jan Houben, Yong Yu q.gao@tudelft.nl @wisdelft