Social, Cultural, and Behavioral Modeling: 13th International Conference, SBP-BRiMS 2020, Washington, DC, USA, October 1821, 2020, Proceedings [Paperback]

This book constitutes the proceedings of the 13th International Conference on Social, Cultural, and Behavioral Modeling, SBP-BRiMS 2020, which was planned to take place in Washington, DC, USA. Due to the COVID-19 pandemic the conference was held online during October 1821, 2020.

The 33 full papers presented in this volume were carefully reviewed and selected from 66 submissions. A wide number of disciplines are represented including computer science, psychology, sociology, communication science, public health, bioinformatics, political science, and organizational science. Numerous types of computational methods are used, such as machine learning, language technology, social network analysis and visualization, agent-based simulation, and statistics.

Beyond Words: Comparing Structure, Emoji Use, and Consistency Across Social Media Posts.- Bot Impacts on Public Sentiment and Community Structures: Comparative Analysis of Three Elections in the Asia-Pacific.- Understanding Colonial Legacy and Environmental Issues in Senegal through Language Use.- Deploying System Dynamics Models for Disease Surveillance in the Philippines.- MDR Cluster-Debias: A Nonlinear Word Embedding Debiasing Pipeline.- Modeling Interventions for Insider Threat.- Validating Social Media Monitoring: Statistical Pitfalls and Opportunities from Public Opinion.- Lying About Lying on Social Media: A Case Study of the 2019 Canadian Elections.- Breadth verses depth: the impact of tree structure on cultural influence.- Optimizing Attention-Aware Opinion Seeding Strategies.- Polarizing Tweets on Climate Change.- Characterizing Sociolinguistic Variation in the Competing Vaccination Communities.- On Countering Disinformation With Caution: Effective Inoculation Strategiesand Others That Backfire Into Community Hyper-Polarization.- Homicidal Event Forecasting and Interpretable Analysis using Hierarchical Attention Model.- Development of a Hybrid Machine Learnlx