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  • © 2020

Putting Social Media and Networking Data in Practice for Education, Planning, Prediction and Recommendation

  • 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

Part of the book series: Lecture Notes in Social Networks (LNSN)

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Table of contents (12 chapters)

  1. Front Matter

    Pages i-xiii
  2. Entering Their World: Using Social Media to Support Students in Modern Times

    • Corinne A. Green, Emily McMillan, Lachlan Munn, Caitlin Sole, Michelle J. Eady
    Pages 15-28
  3. Utilizing Multilingual Social Media Analysis for Food Venue Recommendation

    • Panote Siriaraya, Yuanyuan Wang, Yukiko Kawai, Yusuke Nakaoka, Toyokazu Akiyama
    Pages 29-49
  4. Simplifying E-Commerce Analytics by Discovering Hidden Knowledge in Big Data Clickstreams

    • Konstantinos F. Xylogiannopoulos, Panagiotis Karampelas, Reda Alhajj
    Pages 51-74
  5. User’s Research Interests Based Paper Recommendation System: A Deep Learning Approach

    • Betül Bulut, Esra Gündoğan, Buket Kaya, Reda Alhajj, Mehmet Kaya
    Pages 117-130
  6. Characterizing Behavioral Trends in a Community Driven Discussion Platform

    • Sachin Thukral, Arnab Chatterjee, Hardik Meisheri, Tushar Kataria, Aman Agarwal, Ishan Verma et al.
    Pages 131-149
  7. Mining Habitual User Choices from Google Maps History Logs

    • Iraklis Varlamis, Christos Sardianos, Grigoris Bouras
    Pages 151-175
  8. Semi-Automatic Training Set Construction for Supervised Sentiment Analysis in Polarized Contexts

    • S. Martin-Gutierrez, J. C. Losada, R. M. Benito
    Pages 177-197
  9. Detecting Clickbait on Online News Sites

    • Ayşe Geçkil, Ahmet Anıl Müngen, Esra Gündoğan, Mehmet Kaya
    Pages 199-211

About this book

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.

Editors and Affiliations

  • Computer Engineering, Fırat University, Elazığ, Turkey

    Mehmet Kaya

  • Ministry of Health, Ankara, Turkey

    Şuayip Birinci

  • Department of Computer Science, University of Calgary, Calgary, Canada

    Jalal Kawash, Reda Alhajj

Bibliographic Information

Buy it now

Buying options

eBook USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access