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Topic detection and classification in social networks : the Twitter case / Dimitrios Milioris.
Author
Milioris, Dimitrios
[Browse]
Format
Book
Language
English
Published/Created
Cham, Switzerland : Springer, [2018]
Description
xvi, 105 pages : illustrations (chiefly color) ; 25 cm
Availability
Available Online
Springer Nature - Springer Engineering eBooks 2018 English International
Ebook Central Perpetual, DDA and Subscription Titles
Copies in the Library
Location
Call Number
Status
Location Service
Notes
Engineering Library - Stacks
QA76.9.D343 M54 2018
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Details
Subject(s)
Data mining
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Online social networks
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Twitter
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Summary note
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.
Bibliographic references
Includes bibliographical references and index.
Contents
Introduction
Background and Related Work
Joint Sequence Complexity
Text Classification via Compressive Sensing
Extension of Joint Complexity and Compressive Sensing
Conclusion.
Show 3 more Contents items
ISBN
9783319664132
3319664131
9783319664149 ((e-book))
331966414X
OCLC
1032147362
Statement on language in description
Princeton University Library aims to describe library materials in a manner that is respectful to the individuals and communities who create, use, and are represented in the collections we manage.
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Topic Detection and Classification in Social Networks [electronic resource] : The Twitter Case / by Dimitrios Milioris.
id
99125423493306421