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Putting Social Media and Networking Data in Practice for Education, Planning, Prediction and Recommendation: Lecture Notes in Social Networks

Editat de Mehmet Kaya, Şuayip Birinci, Jalal Kawash, Reda Alhajj
en Limba Engleză Paperback – 28 dec 2020
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 widecoverage, the book forms a good source for practitioners and researchers, including instructors and students.
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Specificații

ISBN-13: 9783030337001
ISBN-10: 3030337006
Ilustrații: XIII, 237 p. 68 illus., 51 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.36 kg
Ediția:1st ed. 2020
Editura: Springer International Publishing
Colecția Springer
Seria Lecture Notes in Social Networks

Locul publicării:Cham, Switzerland

Cuprins

Chapter1: 

Textul de pe ultima copertă

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.

Caracteristici

Demonstrates the power of social media data analysis Features behavior analysis and understanding as important for a variety of applications Forms a good source for practitioners and researchers, including instructors and students