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Topic Detection and Classification in Social Networks

The Twitter Case

  • Dimitrios┬áMilioris

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Dimitrios Milioris
    Pages 1-7
  3. Dimitrios Milioris
    Pages 9-19
  4. Dimitrios Milioris
    Pages 57-67
  5. Dimitrios Milioris
    Pages 93-94
  6. Back Matter
    Pages 95-105

About this book

Introduction

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.

Keywords

Dynamic Social Networks Joint Sequence Complexity Joint Complexity Analytic Combinatorics Analytic Combinatorics Application in Social Networks Compressive Sensing Sparse Representation Kalman Filter Privacy in Social Networks Topic Detection Topic Detection in Social Networks Classification in Social Networks Automatic Classification of Topics Trend Sensing Analysis in Twitter

Authors and affiliations

  • Dimitrios┬áMilioris
    • 1
  1. 1.Massachusetts Institute of Technology CambridgeUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-66414-9
  • Copyright Information Springer International Publishing AG 2018
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-66413-2
  • Online ISBN 978-3-319-66414-9
  • Buy this book on publisher's site