The Journal of Machine Learning Research
Influence and correlation in social networks
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Feedback effects between similarity and social influence in online communities
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
What is Twitter, a social network or a news media?
Proceedings of the 19th international conference on World wide web
Of categorizers and describers: an evaluation of quantitative measures for tagging motivation
Proceedings of the 21st ACM conference on Hypertext and hypermedia
The wisdom in tweetonomies: acquiring latent conceptual structures from social awareness streams
Proceedings of the 3rd International Semantic Search Workshop
Want to be Retweeted? Large Scale Analytics on Factors Impacting Retweet in Twitter Network
SOCIALCOM '10 Proceedings of the 2010 IEEE Second International Conference on Social Computing
Link Creation and Profile Alignment in the aNobii Social Network
SOCIALCOM '10 Proceedings of the 2010 IEEE Second International Conference on Social Computing
Everyone's an influencer: quantifying influence on twitter
Proceedings of the fourth ACM international conference on Web search and data mining
Measuring the dynamic bi-directional influence between content and social networks
ISWC'10 Proceedings of the 9th international semantic web conference on The semantic web - Volume Part I
Tags vs shelves: from social tagging to social classification
Proceedings of the 22nd ACM conference on Hypertext and hypermedia
The bursty dynamics of the Twitter information network
Proceedings of the 23rd international conference on World wide web
| Hi-index | 0.00 |
Social media has become an integral part of today's web and allows communities to share content and socialize. Understanding the factors that influence how communities evolve over time - for example how their social network and their content co-evolve - is an issue of both theoretical and practical relevance. This paper sets out to study the temporal co-evolution of microblog messages' content and social networks on Twitter and of forum-messages' content and social networks induced from communication behavior of users from an online forum called Boards.ie and bi-directional influences between them by using multilevel time series regression models. Our findings suggest that social networks have a stronger influence on content networks in our datasets over time than vice versa, and that social network properties, such as Twitters users' in-degree or Boards.ie users' reply behavior, strongly influence how active and informative users are. While our investigations are limited to three small datasets obtained from Twitter and Boards.ie, our analysis opens up a path towards more systematic studies of network co-evolution on social media platforms. Our results are relevant for researchers and community managers interested in understanding how content-related and social behavior of social media users evolve over time and which factors impact their co-evolution.