Topic detection and classification in social networks : the Twitter case /

Saved in:
Bibliographic Details
Author / Creator:Milioris, Dimitrios, author.
Imprint:Cham, Switzerland : Springer, [2018]
Description:1 online resource
Language:English
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11541904
Hidden Bibliographic Details
ISBN:9783319664149
331966414X
3319664131
9783319664132
9783319664132
Digital file characteristics:text file PDF
Notes:Includes bibliographical references and index.
Online resource; title from PDF title page (EBSCO, viewed October 18, 2017).
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.
Other form:Printed edition: 9783319664132
Standard no.:10.1007/978-3-319-66414-9