Modeling and analysis of real-world (social) networks.
Analysis of social media, viral marketing and the spreading of fake news.
Predictive modeling based on social networks such as box office prediction, election prediction, and ﬂu prediction.
Product adaptation models with social networks such as sale price prediction, new product popularity prediction, brand popularity, and business downfall prediction.
Information diffusion modeling with social networks such as sentiment diffusion in social networks and competitive intelligence.
User modeling and social networks including predicting daily user activities, recurring events, user churn prediction.
Social networks and information/knowledge dissemination such as topic and trend prediction, prediction of information diffusion patterns, and identification of causality and correlation between event/topics/communities.
Social influence analysis on online social networks (systems and algorithms for discovering influential users, recommending influential users in online social networks, social influence maximization, modeling social networks and behavior for discovering influential users, discovering influencers for advertising and viral marketing in social networks and decision support systems).
Trust and reputation in social networks.
New datasets and evaluation methodologies for predictive modeling in social networks.