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

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. Front Matter ....Pages i-xiii Crowd Behavior Modeling in Emergency Evacuation Scenarios Using Belief-Desire-Intention Model (Coşkun Şahin, Reda Alhajj)....Pages 1-14 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 Utilizing Multilingual Social Media Analysis for Food Venue Recommendation (Panote Siriaraya, Yuanyuan Wang, Yukiko Kawai, Yusuke Nakaoka, Toyokazu Akiyama)....Pages 29-49 Simplifying E-Commerce Analytics by Discovering Hidden Knowledge in Big Data Clickstreams (Konstantinos F. Xylogiannopoulos, Panagiotis Karampelas, Reda Alhajj)....Pages 51-74 Event Detection on Communities: Tracking the Change in Community Structure within Temporal Communication Networks (Riza Aktunc, Ismail Hakki Toroslu, Pinar Karagoz)....Pages 75-96 Chasing Undetected Fraud Processes with Deep Probabilistic Networks (Christophe Thovex)....Pages 97-116 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 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 Mining Habitual User Choices from Google Maps History Logs (Iraklis Varlamis, Christos Sardianos, Grigoris Bouras)....Pages 151-175 Semi-Automatic Training Set Construction for Supervised Sentiment Analysis in Polarized Contexts (S. Martin-Gutierrez, J. C. Losada, R. M. Benito)....Pages 177-197 Detecting Clickbait on Online News Sites (Ayşe Geçkil, Ahmet Anıl Müngen, Esra Gündoğan, Mehmet Kaya)....Pages 199-211 A Model-Based Approach for Mining Anomalous Nodes in Networks (Mohamed Bouguessa)....Pages 213-237