Topic Detection and Classification in Social Networks: The Twitter Case

Description

This book provides a novel method for topic detection and classification in social networks. The book addresses several research and technical challenges that are currently being investigated by the research community, from the analysis of relations and communications between members of a community, to quality, authority, relevance and timeliness of the content, traffic prediction based on media consumption, spam detection, to security, privacy and protection of personal information. Furthermore, the book discusses innovative techniques to address those challenges and provides novel solutions based on information theory, sequence analysis and combinatorics, which are applied on real data obtained from Twitter. Front Matter ....Pages i-xvi Introduction (Dimitrios Milioris)....Pages 1-7 Background and Related Work (Dimitrios Milioris)....Pages 9-19 Joint Sequence Complexity: Introduction and Theory (Dimitrios Milioris)....Pages 21-56 Text Classification via Compressive Sensing (Dimitrios Milioris)....Pages 57-67 Extension of Joint Complexity and Compressive Sensing (Dimitrios Milioris)....Pages 69-92 Conclusions and Perspectives (Dimitrios Milioris)....Pages 93-94 Back Matter ....Pages 95-105