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Putting social media and networking ...

Kaya, Mehmet.

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

Record Type:	Electronic resources : Monograph/item
Title/Author:	Putting social media and networking data in practice for education, planning, prediction and recommendationedited by Mehmet Kaya ... [et al.].
other author:	Kaya, Mehmet.
Published:	Cham :Springer International Publishing :2020.
Description:	xiii, 237 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Online social networks.
Online resource:	https://doi.org/10.1007/978-3-030-33698-1
ISBN:	9783030336981$q(electronic bk.)

Putting social media and networking data in practice for education, planning, prediction and recommendation
Putting social media and networking data in practice for education, planning, prediction and recommendation[electronic resource] /edited by Mehmet Kaya ... [et al.]. - Cham :Springer International Publishing :2020. - xiii, 237 p. :ill., digital ;24 cm. - Lecture notes in social networks,2190-5428. - Lecture notes in social networks..

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.

ISBN: 9783030336981$q(electronic bk.)

Standard No.: 10.1007/978-3-030-33698-1doiSubjects--Topical Terms:

281852
Online social networks.

LC Class. No.: HM742 / .P888 2020

Dewey Class. No.: 006.754

Putting social media and networking data in practice for education, planning, prediction and recommendation
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490 1 $a Lecture notes in social networks, $x 2190-5428
520 $a 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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