A mathematical theory of communication
ACM SIGMOBILE Mobile Computing and Communications Review
Multi-document summarization using off the shelf compression software
HLT-NAACL-DUC '03 Proceedings of the HLT-NAACL 03 on Text summarization workshop - Volume 5
Foundations and Trends in Information Retrieval
Tweet the debates: understanding community annotation of uncollected sources
WSM '09 Proceedings of the first SIGMM workshop on Social media
Characterizing debate performance via aggregated twitter sentiment
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Unsupervised modeling of Twitter conversations
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Classifying latent user attributes in twitter
SMUC '10 Proceedings of the 2nd international workshop on Search and mining user-generated contents
Robust sentiment detection on Twitter from biased and noisy data
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Twitinfo: aggregating and visualizing microblogs for event exploration
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Part-of-speech tagging for Twitter: annotation, features, and experiments
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
Overview of the third international workshop on search and mining user-generated contents
Proceedings of the 20th ACM international conference on Information and knowledge management
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This contribution proposes a framework to generate auxiliary rich TV content metadata by processing social networks data. Based on simple criteria to identify authoritative social media sources, we have analysed Twitter short messages relative to TV program content and devised a method to compute their informative value. We have extracted dozen of features and characterized such social data in terms of quality and relevancy. This is a first step towards integrating relevant social media information to enhance the description of TV content as well as for generating recommendations based on social data.