BESC 2023 invites submissions of original, high-quality research papers addressing cutting-edge developments from all areas of behavioural and social computing. The conference aims to bring together researchers and practitioners from academia and industry to share their knowledge, experience, and perspectives on the latest trends, challenges, and opportunities in this rapidly evolving field. Topics of interest include, but are not limited to:

Social Computing, Computational Social Science and Applications

    Computational models of social phenomena
    Social behaviour
    Social network analysis
    Semantic web
    Collective intelligence
    Security, privacy, trust in social contexts
    Social recommendation
    Social influence and social contagions
    Quantifying offline phenomena through online data
    Forecasting of social phenomena
    Science and technology studies approaches to computational social science
    Social media and health behaviours
    Social psychology and personality
    New theories, methods, and objectives in computational social science

Digital Humanities

    Digital media
    Digital humanities
    Digital games and learning
    Digital footprints and privacy
    Crowd dynamics
    Digital arts
    Digital healthcare
    Activity streams and experience design
    Virtual communities (e.g., open-source, multiplayer gaming, etc.)

Information Management and Information Systems (IS)

    Decision analytics
    E-Business
    Decision analytics
    Computational finance
    Societal impacts of IS
    Human behaviour and IS
    IS in healthcare
    IS security and privacy
    IS strategy, structure and organizational impacts
    Service science and IS

Natural Language Processing

    Web mining and its social interpretations
    Sentiment Analysis, Stylistic Analysis, and Argument Mining
    Opinion mining and social media analytics
    Credibility of online content
    Computational Linguistics
    Mining big social data
    Cognitive Modelling and Psycholinguistics

Behaviour and User Modelling, Privacy, and Ethics

    Behaviour change
    Positive technology
    Personalization for individuals, groups and populations
    Large scale personalization, adaptation and recommendation
    Web dynamics and personalization
    Privacy, perceived security and trust
    Technology and Wellbeing
    Ethics of computational research on human behaviour

Technology Enhanced Learning (TEL)

    E-Learning and M-Learning
    Open and Distance Learning
    User modeling and personalization in TEL
    TEL in secondary and in higher education
    New tools for TEL