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

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

  1. 1. A Comparative Study of Users’Microblogging Behavior on Sina Weiboand TwitterUMAP, Montréal, July 2012 Qi Gao1, Fabian Abel1, Geert-Jan Houben1,Yong Yu2 1 Web Information Systems, Delft University of Technology 2 APEX lab, Shanghai Jiao Tong University Delft University of Technology
  2. 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 2 Microblogging Behavior on Sina Weibo and Twitter
  3. 3. Cultural differences standing up for himself acting as a member of a groupFlickr:semicharmed Flickr:webei 3 Microblogging Behavior on Sina Weibo and Twitter
  4. 4. Data sources follower/followee network limited length of a post repost/reply/like use of URLs and hashtags meta information (time, source) 4 Microblogging Behavior on Sina Weibo and Twitter
  5. 5. User modeling and analysis framework syntactic analysis sentiment analysis Cultural Analytics semantic analysis temporal analysis Data Processing and User Profiling data acquisition multilingual NER metadata extraction semantic enrichment topic/interest modeling user profile construction Microblogging Platforms Semantic Web 5 Microblogging Behavior on Sina Weibo and Twitter
  6. 6. User profiling Profile What could go wrong? RT ? @DRUGE_REPORT Washington: White House seeks ‘Control’ over communication during ‘crisis’ #obama drudge.tw/LVZygj 6 Microblogging Behavior on Sina Weibo and Twitter
  7. 7. User profiling – syntactic characteristics Profile What could go wrong? RT # hashtag/URL @DRUGE_REPORT Washington: White House seeks ‘Control’ over communication during ‘crisis’ #obama drudge.tw/LVZygj 7 Microblogging Behavior on Sina Weibo and Twitter
  8. 8. User profiling – semantic characteristics Profile What could go wrong? RT # hashtag/URL @DRUGE_REPORT entity Washington: White House seeks ‘Control’ over communication during ‘crisis’ #obama drudge.tw/LVZygj 8 Microblogging Behavior on Sina Weibo and Twitter
  9. 9. User profiling – semantic characteristics Profile What could go wrong? RT # hashtag/URL @DRUGE_REPORT entity Washington: White House seeks ‘Control’ over T topic communication during ‘crisis’ #obama drudge.tw/LVZygj topic:person topic:location topic:organization 9 Microblogging Behavior on Sina Weibo and Twitter
  10. 10. User profiling – sentiment characteristics Profile What could go wrong? RT # hashtag/URL @DRUGE_REPORT entity Washington: White House seeks ‘Control’ over T topic communication during ‘crisis’ sentiment #obama drudge.tw/LVZygj positive negative neutral 10 Microblogging Behavior on Sina Weibo and Twitter
  11. 11. User profiling – temporal characteristics Profile What could go wrong? RT # hashtag/URL @DRUGE_REPORT entity Washington: White House seeks ‘Control’ over T topic communication during ‘crisis’ sentiment #obama drudge.tw/LVZygj temporal information 11 Microblogging Behavior on Sina Weibo and Twitter
  12. 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) 12 Microblogging Behavior on Sina Weibo and Twitter
  13. 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 nationalitiesgeert-hofstede.com 13 Microblogging Behavior on Sina Weibo and Twitter
  14. 14. Syntactic analysis – what are the syntactical characteristics of messages? hashtags/URLs per post Hashtag-Weibo hashtag-Twitter URL-Weibo URL-Twitter avg. number of 1 Hashtag-Twitter URL-Twitter 0.1 0.01 URL-Weibo hashtag-Weibo 0 0% 20% 40% 60% 80% 100% usersHashtags and URLs are less Users on Twitter are more triggered byfrequently applied on Sina hashtags and URLs when propagatingWeibo than on Twitter. information than on Sina Weibo. 14 Microblogging Behavior on Sina Weibo and Twitter
  15. 15. Syntactic analysis – what are the syntactical characteristics of messages? high collectivism Cultural high individualism (Sina Weibo) Differences (Twitter)Hashtags and URLs are less Users on Twitter are more triggered byfrequently applied on Sina hashtags and URLs when propagatingWeibo than on Twitter. information than on Sina Weibo. 15 Microblogging Behavior on Sina Weibo and Twitter
  16. 16. Semantic analysis – what kind of topics are discussed? avg. number of entities per post 10 Weibo Weibo 1 Twitter 0.1 Twitter 0.01 0.001 0 0% 20% 40% 60% 80% 100% users 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). 16 Microblogging Behavior on Sina Weibo and Twitter
  17. 17. Semantic analysis – what kind of topics are discussed? high collectivism Cultural high individualism (Sina Weibo) Differences (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 Microblogging Behavior on Sina Weibo and Twitter
  18. 18. Sentiment analysis – what are the sentimentcharacteristics of microposts? Weibo 100% ratio of positve posts Weibo 80% Twitter Twitter 60% more positive posts more negative posts 40% 20% 0% 0% 20% 40% 60% 80% 100% users Sina Weibo users have a stronger tendency to publish positive messages than Twitter users. 18 Microblogging Behavior on Sina Weibo and Twitter
  19. 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. 19 Microblogging Behavior on Sina Weibo and Twitter
  20. 20. Combining semantic and sentiment analysislong-term orientation Cultural short-tem orientation Differences (Sina Weibo) (Twitter) The difference is amplified when discussing ‘people’ or ‘location’, with Sina Weibo users even more positive and Twitter users more negative. 20 Microblogging Behavior on Sina Weibo and Twitter
  21. 21. Temporal analysis – how quickly do users propagate information?time distance (in hours) Weibo Weibo 1000 Twitter 100 10 1 Twitter time distance = 0.1 trepost - toriginal post 0 0% 20% 40% 60% 80% 100% users Twitter users repost messages faster than Sina Weibo users. 21 Microblogging Behavior on Sina Weibo and Twitter
  22. 22. Temporal analysis – how quickly do users propagateinformation? large degree of Cultural low degree of power distance Differences power distance (Sina Weibo) (Twitter) Twitter users repost messages faster than Sina Weibo users. 22 Microblogging Behavior on Sina Weibo and Twitter
  23. 23. Qi Gao et al. Information Propagation Cultures on Sina Weibo and Twitter. InProceedings of ACM Web Science Conference 2012. Evanston, USA. 23 Microblogging Behavior on Sina Weibo and Twitter
  24. 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 24 Microblogging Behavior on Sina Weibo and Twitter
  25. 25. Thank You! Q&AQi Gao, Fabian Abel, Geert-Jan Houben, Yong Yu q.gao@tudelft.nl @wisdelft 25 Microblogging Behavior on Sina Weibo and Twitter
  26. 26. Interpretation Individualism Cultural /Collectivism DifferencesTwitter users seem to bemore eager to let their postsappear in the publicdiscussion – possibly a higherdemand to profile themselves(individualism) 26 Microblogging Behavior on Sina Weibo and Twitter
  27. 27. Interpretation Individualism Cultural /Collectivism DifferencesThe finding is in line with thelow commitment to anorganization in China, which isone of the typical indicator fora highly collectivist culture. 27 Microblogging Behavior on Sina Weibo and Twitter
  28. 28. Interpretation Long Term Cultural Orientation DifferencesThe positive nature of theinformation on Sina Weibomight point at the long termorientation that is attributedto the Chinese culture. 28 Microblogging Behavior on Sina Weibo and Twitter
  29. 29. Interpretation Power Cultural Distance DifferencesTwitter users may have theimpression that they play animportant role in theinformation propagationprocess, i.e. they act as if theyare in the power of spreadinginformation (power distance). 29 Microblogging Behavior on Sina Weibo and Twitter

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