The rapid proliferation of digital platforms has generated vast volumes of social behavioral data, offering unprecedented opportunities to study human interactions, decision-making, and societal trends. However, extracting meaningful insights from such data requires sophisticated models that harmonize data-driven patterns with domain-specific knowledge. Traditional AI approaches often struggle to contextualize raw behavioral data, while knowledge-based systems may lack adaptability to dynamic real-world scenarios. This special session aims to bridge this gap by exploring hybrid AI models that integrate structured knowledge (e.g., psychological theories, sociological frameworks) with data-driven techniques (e.g., machine learning, deep learning) to advance the understanding of social behaviors.

The primary objectives of this special session are advancing the frontiers of developing models that synergize knowledge representation (e.g., ontologies, rules) with data-driven and Large Language Model (LLM)-Driven methods to enhance interpretability, robustness, and accuracy in behavioral analysis. The special session also seeks to explore domain applications by Highlighting case studies where knowledge + data-driven AI improves social behavioral insights in sectors like healthcare, education, social media, and policy-making.

The special session invites submissions addressing (but not limited to) the following areas:

  • Theoretical Foundations
    • Knowledge representation for social behavioral data (e.g., ontologies, semantic networks).
    • Explainable AI (XAI) frameworks for behavioral modeling.
    • Cognitive computing approaches to simulate human decision-making.
  • Methodological Innovations
    • Hybrid models combining knowledge graphs with neural networks for behavior prediction.
    • Multi-source data fusion (text, sensor, social media) guided by domain knowledge.
    • Knowledge-enhanced reinforcement learning for behavioral interventions.
    • Transfer learning across behavioral datasets using shared knowledge bases.
  • Applications in Social Domains
    • Mental health: Early detection of disorders via social media analysis.
    • Education: Personalized learning systems using behavioral analytics.
    • Social media: Misinformation detection and user engagement optimization.
    • Policy-making: Data-driven insights for urban planning or public health.
  • Ethical and Societal Considerations
    • Bias mitigation in behavioral AI models.
    • Privacy-preserving techniques for sensitive behavioral data.
    • Legal and ethical frameworks for deploying behavioral AI systems.
  • Surveys and Future Directions
    • Systematic reviews of knowledge + data-driven AI in social computing.
    • Benchmarking datasets and evaluation metrics for behavioral AI.
    • Speculations on next-generation AI paradigms for social behavioral understanding.

Important Dates

  • Special Session Papers Submission: 15 July 2025
  • Acceptance Notification: 15 August 2025
  • Author Registration: 1 September 2025
  • Camera-Ready Submission: 1 September 2025
  • Conference Date: 16-18 Oct 2025

Paper submission instruction

Paper submission system is available at: https://cmt3.research.microsoft.com/BESC2025.

All papers will be reviewed by the Program Committee on the basis of technical quality, relevance to BESC 2025, originality, significance and clarity.

Please note:

  • All submissions should use IEEE two-column style. Templates are available from here.
  • All papers must be submitted electronically through the paper submission system in PDF format only. BESC 2025 accepts special session papers in 6 pages. The page count excludes the references.
  • Paper review will be double-blind, and submissions not properly anonymized will be desk-rejected without review.
  • Submitted papers must not substantially overlap with papers that have been published or that are simultaneously submitted to a journal or a conference with proceedings.
  • Papers must be clearly submitted in English and will be selected based on their originality, timeliness, significance, relevance, and clarity of presentation.
  • Submission of a paper should be regarded as a commitment that, should the paper be accepted, at least one of the authors will register and attend the conference to present the work.
  • Accepted papers will be submitted for inclusion into IEEE Xplore subject to meeting IEEE Xplore’s scope and quality requirements and indexed by EI. Top quality papers after presented in the conference will be selected for extension and publication in several special issues of international journals, e.g., World Wide Web Journal (Springer), Web Intelligence (IOS Press), Social Network Analysis and Mining (Springer), Human-Centric Intelligent Systems (Springer), Natural Language Processing (Elsevier), etc.
  • The use of artificial intelligence (AI)–generated text in an article shall be disclosed in the acknowledgements section of any paper submitted to an IEEE Conference or Periodical. The sections of the paper that use AI-generated text shall have a citation to the AI system used to generate the text.

Organizing Committee

Special Session Chairs
  • Dr. Yifan Zhu, Beijing University of Posts and Telecommunications, China
  • Dr. Qika Lin, National University of Singapore, Singapore

Program Committee Members
  • Prof. Qi Zhang, Tongji University, China
  • Prof. Haihong E, Beijing University of Posts and Telecommunications, China
  • Prof. Xuesong Li, Beijing Institute of Technology, China
  • Prof. Fuquan Zhang, Minjiang University, China
  • Dr. Yangliao Geng, Beijing Jiaotong University, China
  • Dr. Wei Fan, Oxford University, United Kingdom
  • Dr. James Chambua, University of Dar es Salaam, Tanzania
  • Dr. Hao Lu, Institute of Automation Chinese Academy of Sciences, China
  • Dr. Yuandong Wang, Tsinghua Univeristy, China
  • Dr. Guijin Li, University of Toronto, Canada