Influence and Behavior Analysis in Social Networks and Social Media

1. Front Matter

   Pages i-vi

   PDF

2. Social Network to Improve the Educational Experience with the Deployment of Different Learning Models

   • Paúl Esteban Vintimilla-Tapia, Jack Fernando Bravo-Torres, Pablo Leonidas Gallegos-Segovia, Esteban Fernando Ordóñez-Morales, Martín López-Nores, Yolanda Blanco-Fernández

   Pages 1-25

3. Temporal Model of the Online Customer Review Helpfulness Prediction with Regression Methods

   • Shih-Hung Wu, Yi-Hsiang Hsieh, Liang-Pu Chen, Ping-Che Yang, Liu Fanghuizhu

   Pages 27-38

4. Traits of Leaders in Movement Initiation: Classification and Identification

   • Chainarong Amornbunchornvej, Margaret C. Crofoot, Tanya Y. Berger-Wolf

   Pages 39-62

5. Emotional Valence Shifts and User Behavior on Twitter, Facebook, and YouTube

   • Ema Kušen, Mark Strembeck, Mauro Conti

   Pages 63-83

6. Diffusion Algorithms in Multimedia Social Networks: A Novel Model

   • Flora Amato, Vincenzo Moscato, Antonio Picariello, Giancarlo Sperlí

   Pages 85-103

7. Detecting Canadian Internet Satisfaction by Analyzing Twitter Accounts of Shaw Communications

   • Satara Cressy, B. L. Pham, Hannah Wright, Reda Alhajj

   Pages 105-126

8. Editing Behavior Analysis for Predicting Active and Inactive Users in Wikipedia

   • Harish Arelli, Francesca Spezzano, Anu Shrestha

   Pages 127-147

9. Incentivized Social Sharing: Characteristics and Optimization

   • Joseph J. Pfeiffer III, Elena Zheleva

   Pages 149-174

10. Rumor Source Detection in Finite Graphs with Boundary Effects by Message-Passing Algorithms

    • Pei-Duo Yu, Chee Wei Tan, Hung-Lin Fu

    Pages 175-192

11. Robustness of Influence Maximization Against Non-adversarial Perturbations

    • Sho Tsugawa, Hiroyuki Ohsaki

    Pages 193-210

12. Analyzing Social Book Reading Behavior on Goodreads and How It Predicts Amazon Best Sellers

    • Suman Kalyan Maity, Abhishek Panigrahi, Animesh Mukherjee

    Pages 211-235

This timely book focuses on influence and behavior analysis in the broader context of social network applications and social media.  Twitter accounts of telecommunications companies are analyzed.  Rumor sources in finite graphs with boundary effects by message-passing algorithms are identified.

The coherent, state-of-the-art collection of chapters was initially selected based on solid reviews from the IEEE/ACM International Conference on Advances in Social Networks, Analysis, and Mining (ASONAM '17). Chapters were then improved and extended substantially, and the final versions were rigorously reviewed and revised to meet the series standards. Original chapters coming from outside of the meeting round out the coverage. The result will appeal to researchers and students working in social network and social media analysis.

• Social Network Analysis and Mining
• Influence Analysis
• Recommendation Systems
• twitter analysis shaw communications
• ASONAM 2017
• misuse of social media
• Analyzing Twitter Accounts
• Social Book Reading Behavior
• Predicting 'Amazon Best Sellers'
• computational social sciences

• Department of Computer Engineering, Firat University, Elazig, Türkiye

  Mehmet Kaya

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

  Reda Alhajj

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