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Putting social media and networking data in practice for education, planning, prediction and recommendation

This book focusses on recommendation, behavior, and anomaly, among of social media analysis. First, recommendation is vital for a variety of applications to narrow down the search space and to better guide people towards educated and personalized alternatives. In this context, the book covers suppor...

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Detalles Bibliográficos
Autores principales: Kaya, Mehmet, Birinci, Şuayip, Kawash, Jalal, Alhajj, Reda
Lenguaje:eng
Publicado: Springer 2020
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-3-030-33698-1
http://cds.cern.ch/record/2706759
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author Kaya, Mehmet
Birinci, Şuayip
Kawash, Jalal
Alhajj, Reda
author_facet Kaya, Mehmet
Birinci, Şuayip
Kawash, Jalal
Alhajj, Reda
author_sort Kaya, Mehmet
collection CERN
description This book focusses on recommendation, behavior, and anomaly, among of social media analysis. First, recommendation is vital for a variety of applications to narrow down the search space and to better guide people towards educated and personalized alternatives. In this context, the book covers supporting students, food venue, friend and paper recommendation to demonstrate the power of social media data analysis. Secondly, this book treats behavior analysis and understanding as important for a variety of applications, including inspiring behavior from discussion platforms, determining user choices, detecting following patterns, crowd behavior modeling for emergency evacuation, tracking community structure, etc. Third, fraud and anomaly detection have been well tackled based on social media analysis. This has is illustrated in this book by identifying anomalous nodes in a network, chasing undetected fraud processes, discovering hidden knowledge, detecting clickbait, etc. With this wide coverage, the book forms a good source for practitioners and researchers, including instructors and students.
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spelling cern-27067592021-04-21T18:11:47Zdoi:10.1007/978-3-030-33698-1http://cds.cern.ch/record/2706759engKaya, MehmetBirinci, ŞuayipKawash, JalalAlhajj, RedaPutting social media and networking data in practice for education, planning, prediction and recommendationComputing and ComputersThis book focusses on recommendation, behavior, and anomaly, among of social media analysis. First, recommendation is vital for a variety of applications to narrow down the search space and to better guide people towards educated and personalized alternatives. In this context, the book covers supporting students, food venue, friend and paper recommendation to demonstrate the power of social media data analysis. Secondly, this book treats behavior analysis and understanding as important for a variety of applications, including inspiring behavior from discussion platforms, determining user choices, detecting following patterns, crowd behavior modeling for emergency evacuation, tracking community structure, etc. Third, fraud and anomaly detection have been well tackled based on social media analysis. This has is illustrated in this book by identifying anomalous nodes in a network, chasing undetected fraud processes, discovering hidden knowledge, detecting clickbait, etc. With this wide coverage, the book forms a good source for practitioners and researchers, including instructors and students.Springeroai:cds.cern.ch:27067592020
spellingShingle Computing and Computers
Kaya, Mehmet
Birinci, Şuayip
Kawash, Jalal
Alhajj, Reda
Putting social media and networking data in practice for education, planning, prediction and recommendation
title Putting social media and networking data in practice for education, planning, prediction and recommendation
title_full Putting social media and networking data in practice for education, planning, prediction and recommendation
title_fullStr Putting social media and networking data in practice for education, planning, prediction and recommendation
title_full_unstemmed Putting social media and networking data in practice for education, planning, prediction and recommendation
title_short Putting social media and networking data in practice for education, planning, prediction and recommendation
title_sort putting social media and networking data in practice for education, planning, prediction and recommendation
topic Computing and Computers
url https://dx.doi.org/10.1007/978-3-030-33698-1
http://cds.cern.ch/record/2706759
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AT birincisuayip puttingsocialmediaandnetworkingdatainpracticeforeducationplanningpredictionandrecommendation
AT kawashjalal puttingsocialmediaandnetworkingdatainpracticeforeducationplanningpredictionandrecommendation
AT alhajjreda puttingsocialmediaandnetworkingdatainpracticeforeducationplanningpredictionandrecommendation