Clustering Algorithms
You Are Who You Talk To: Detecting Roles in Usenet Newsgroups
HICSS '06 Proceedings of the 39th Annual Hawaii International Conference on System Sciences - Volume 03
Query independent measures of annotation and annotator impact
Proceedings of the WSDM '09 Workshop on Exploiting Semantic Annotations in Information Retrieval
Clustering of time series data-a survey
Pattern Recognition
Experiments for the number of clusters in K-means
EPIA'07 Proceedings of the aritficial intelligence 13th Portuguese conference on Progress in artificial intelligence
Patterns of temporal variation in online media
Proceedings of the fourth ACM international conference on Web search and data mining
Extracting Social Networks to Understand Interaction
ASONAM '11 Proceedings of the 2011 International Conference on Advances in Social Networks Analysis and Mining
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Social media has become an integral part of the web, and its popularity continues to provide an outlet for people's opinions and discussion about any topic of interest. In this paper we examine the interest around a number of television series that are broadcast on a weekly basis. Our aim is to show that by observing solely the initial interactions of fans or users of a web forum, we can extrapolate the longer-term interest in particular episodes. We do so by observing the temporal dynamics of the conversation, and performing a clustering so as to judge how much time is required before reasonable conclusions can be drawn about the level of interest surrounding an episode. We find that early interaction trends have strong similarities with the overall conversation patterns.