Positive and negative behavioral analysis in social networks

Abstract

Use of online social networks has grown dramatically since the first Web 2.0 technologies were deployed in the early 2000s. Our ability to capture user data, in particular behavioral data has grown in concert with increased use of these social systems. In this study, we survey methods for modeling and analyzing online user behavior. We focus on negative behaviors (social spamming and cyberbullying) and mitigation techniques for these behaviors. We also provide information on the interplay between privacy and deception in social networks and conclude by looking at trending and cascading models in social media. WIREs Data Mining Knowl Discov 2017, 7:e1203. doi: 10.1002/widm.1203

Document Details

Document Type
Pub Defense Publication
Publication Date
Mar 27, 2017
Source ID
10.1002/widm.1203

Entities

People

  • Anna Squicciarini
  • Christopher Griffin
  • Sarah Rajtmajer

Organizations

  • Army Research Office
  • National Science Foundation
  • Pennsylvania State University
  • United States Naval Academy

Tags

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Computational Modeling and Simulation
  • Nanofabrication and Microfabrication.

Technology Areas

  • AI & ML