a comparative study of users' microblogging behavior on sina weibo and twitter

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  • 1.A Comparative Study of UsersMicroblogging Behavior on Sina Weiboand TwitterUMAP, Montral, July 2012Qi Gao1, Fabian Abel1, Geert-Jan Houben1,Yong Yu2 1 Web Information Systems, Delft University of Technology2 APEX lab, Shanghai Jiao Tong University Delft University of Technology

2. What we study: microblogging behavior 340,000,000 100,000,000 500,000,000 250,000,000What are the differences in Chinese andWestern users microblogging behavior?Wikipedia:Twitter Wikipedia:Sina_Weibo2 Microblogging Behavior on Sina Weibo and Twitter 3. Cultural differencesstanding up for himself acting as a member of a groupFlickr:semicharmed Flickr:webei3 Microblogging Behavior on Sina Weibo and Twitter 4. Data sourcesfollower/followeenetworklimited length ofa postrepost/reply/likeuse of URLsand hashtagsmeta information(time, source) 4 Microblogging Behavior on Sina Weibo and Twitter 5. User modeling and analysis framework syntactic analysissentiment analysis Cultural Analyticssemantic analysistemporal analysisData Processing and User Profilingdata acquisitionmultilingual NERmetadata extraction semantic enrichment topic/interest modeling user profile constructionMicroblogging PlatformsSemantic Web5 Microblogging Behavior on Sina Weibo and Twitter 6. User profilingProfile 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. User profiling syntactic characteristics ProfileWhat could go wrong? RT #hashtag/URL@DRUGE_REPORTWashington: White Houseseeks Control overcommunication during crisis#obama drudge.tw/LVZygj7 Microblogging Behavior on Sina Weibo and Twitter 8. User profiling semantic characteristics ProfileWhat could go wrong? RT #hashtag/URL@DRUGE_REPORT entityWashington: White Houseseeks Control overcommunication during crisis#obama drudge.tw/LVZygj8 Microblogging Behavior on Sina Weibo and Twitter 9. User profiling semantic characteristicsProfileWhat could go wrong? RT#hashtag/URL@DRUGE_REPORTentityWashington: White Houseseeks Control overT topiccommunication during crisis#obama drudge.tw/LVZygjtopic:persontopic:locationtopic:organization 9 Microblogging Behavior on Sina Weibo and Twitter 10. User profiling sentiment characteristicsProfile What could go wrong? RT #hashtag/URL @DRUGE_REPORTentity Washington: White House seeks Control over T topic communication during crisis sentiment #obama drudge.tw/LVZygjpositivenegativeneutral 10 Microblogging Behavior on Sina Weibo and Twitter 11. User profiling temporal characteristicsProfile What could go wrong? RT #hashtag/URL @DRUGE_REPORTentity Washington: White House seeks Control overTtopic communication during crisis sentiment #obama drudge.tw/LVZygjtemporal information 11 Microblogging Behavior on Sina Weibo and Twitter 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 (Hofstedes cultural dimensions) 12 Microblogging Behavior on Sina Weibo and Twitter 13. Cultural model: Hofstedes 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. Syntactic analysis what are the syntactical characteristics of messages?hashtags/URLs per postHashtag-Weibo hashtag-TwitterURL-WeiboURL-Twitteravg. number of1 Hashtag-TwitterURL-Twitter 0.1 0.01 URL-Weibo hashtag-Weibo0 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. Syntactic analysis what are the syntactical characteristics of messages?high collectivism Culturalhigh individualism(Sina Weibo) Differences(Twitter)Hashtags and URLs are lessUsers on Twitter are more triggered byfrequently applied on Sinahashtags and URLs when propagatingWeibo than on Twitter.information than on Sina Weibo.15 Microblogging Behavior on Sina Weibo and Twitter 16. Semantic analysis what kind of topics are discussed? avg. number of entities per post10WeiboWeibo 1Twitter0.1Twitter 0.010.001 00% 20% 40% 60% 80% 100%usersThe topics that users discuss on Sina Weibo are to a largeextent related to locations and persons. In contrast to SinaWeibo, users on Twitter are talking more aboutorganizations (such as companies, political parties). 16 Microblogging Behavior on Sina Weibo and Twitter 17. Semantic analysis what kind of topics are discussed? high collectivismCultural high individualism (Sina Weibo)Differences (Twitter)The topics that users discuss on Sina Weibo are to a largeextent related to locations and persons. In contrast to SinaWeibo, users on Twitter are talking more aboutorganizations (such as companies, political parties).17 Microblogging Behavior on Sina Weibo and Twitter 18. Sentiment analysis what are the sentimentcharacteristics of microposts?Weibo100%ratio of positve postsWeibo 80TwitterTwitter 60%more positive postsmore 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. 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. 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. Temporal analysis how quickly do users propagateinformation?time distance (in hours) WeiboWeibo 1000 Twitter 10010 1Twitter time distance = 0.1 trepost - toriginal post 0 0% 20% 40% 60% 80% 100% usersTwitter users repost messages faster thanSina Weibo users.21 Microblogging Behavior on Sina Weibo and Twitter 22. Temporal analysis how quickly do users propagateinformation?large degree ofCulturallow degree ofpower distanceDifferences power distance(Sina Weibo) (Twitter) Twitter users repost messages faster than Sina Weibo users.22 Microblogging Behavior on Sina Weibo and Twitter 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. 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 factors24 Microblogging Behavior on Sina Weibo and Twitter 25. Thank You!Q&AQi Gao, Fabian Abel, Geert-Jan Houben, Yong Yuq.gao@tudelft.nl@wisdelft 25 Microblogging Behavior on Sina Weibo and Twitter 26. Interpretation Individualism Cultural /CollectivismDifferencesTwitter 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. Interpretation Individualism Cultural /CollectivismDifferencesThe 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. Interpretation Long Term Cultural OrientationDifferencesThe 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. InterpretationPower Cultural DistanceDifferencesTwitter 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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