Data mining: concepts and techniques
Data mining: concepts and techniques
Information diffusion through blogspace
Proceedings of the 13th international conference on World Wide Web
Tracking Information Epidemics in Blogspace
WI '05 Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence
Yes, there is a correlation: - from social networks to personal behavior on the web
Proceedings of the 17th international conference on World Wide Web
Characterizing social cascades in flickr
Proceedings of the first workshop on Online social networks
A measurement-driven analysis of information propagation in the flickr social network
Proceedings of the 18th international conference on World wide web
What is Twitter, a social network or a news media?
Proceedings of the 19th international conference on World wide web
Inferring networks of diffusion and influence
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Challenges in measuring online advertising systems
IMC '10 Proceedings of the 10th ACM SIGCOMM conference on Internet measurement
The impact of YouTube recommendation system on video views
IMC '10 Proceedings of the 10th ACM SIGCOMM conference on Internet measurement
Who says what to whom on twitter
Proceedings of the 20th international conference on World wide web
Information spreading in context
Proceedings of the 20th international conference on World wide web
Broadcast yourself: understanding YouTube uploaders
Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference
YouTube around the world: geographic popularity of videos
Proceedings of the 21st international conference on World Wide Web
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According to the classical communication theories, known as Gate keeping and Selective Exposure, individuals tend to have selective behavior when they disseminate and receive information based on their psychological preferences. Selective behavior related to these two theories have been broadly studied separately. While, thanks to the advent of Online Social Networks (OSNs), larger-scale feedback and user information can be collected. In this paper, based on these data, We analyze the correlation among users' properties (such as age, gender, and cultural background) and analyze their selective behavior by tagging users as disseminators and/or audiences in YouTube, Flickr, and Twitter. We find that despite enormous amount of content available in OSNs, users have a comparatively small selective range and do exhibit selective behavior properties. In particular, they pay the most attention to the content published by disseminators that share similar properties, i.e., gender, age, and country. Nonetheless, we also find significant differences and commonalities among the three OSNs with respect to selective behavior. In particular, (i) the proportion and properties of disseminators, audiences, and dual-role users are quite different for the three networks, (ii) the global level of information spread in Flickr is almost two times than that in Twitter and YouTube is approximately the median one, (iii) For a given country, the global level of information spread is different for different OSNs. For a given OSN, it is different for different countries, (iv) despite ubiquitous presence of dual-role users in OSNs, most of such users are very active as either disseminators or audiences, but not both. Our findings are not only useful for understanding these two theories, but also have applications ranging from advertising and recommendation systems to developing predicting models.