Topic detection and classification in social networks : the Twitter case /
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,...
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Main Authors: | |
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Published: |
Springer,
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Publisher Address: | Cham, Switzerland : |
Publication Dates: | [2018] |
Literature type: | Book |
Language: | English |
Subjects: | |
Summary: |
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. |
Carrier Form: | xvi, 105 pages : illustrations (chiefly color) ; 25 cm |
Bibliography: | Includes bibliographical references (pages 97-101) and index. |
ISBN: |
9783319664132 3319664131 |
Index Number: | QA76 |
CLC: | TP391.3 |
Call Number: | TP391.3/M644 |
Contents: | Introduction -- Background and Related Work -- Joint Sequence Complexity -- Text Classification via Compressive Sensing -- Extension of Joint Complexity and Compressive Sensing -- Conclusion. |