Flex Conference (Physical / Digital)

International Conference on Computational Social Science and Network Modeling - (ICCSSNM-27)

13th - 14th January 2027 , Serrekunda - Gambia

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Call For Papers

The (ICCSSNM-27) emphasizes interdisciplinary collaboration by bringing together experts from diverse fields. It encourages research that integrates multiple perspectives to address complex global challenges.

Key areas such as Computational Science, Data Science are explored to promote cross-domain knowledge exchange and collaborative innovation.

Authors are invited to submit papers addressing, but not limited to, the following areas:

  • Computational methods in social science
  • Network modeling techniques for social data
  • Big data analytics in social research
  • Machine learning applications in social sciences
  • Social network analysis and visualization
  • Ethics in computational social science
  • Data-driven approaches to social issues
  • Impact of social media on society
  • Interdisciplinary research in social sciences
  • Predictive modeling in social behavior
  • Challenges in social data collection
  • Case studies in computational social science
  • Real-time analysis of social networks
  • Data privacy concerns in social research
  • Social dynamics and computational modeling
  • Role of AI in understanding social phenomena
  • Collaborative tools for social science research
  • Future trends in computational social science
  • Quantitative methods in social research
  • Data sharing and collaboration in social sciences

Assessment

All submissions will undergo peer review to ensure quality and interdisciplinary relevance. Accepted papers will be presented and considered for publication in journals and conference proceedings.

Registration

Registering for the conference provides access to keynote sessions, technical presentations, and networking opportunities with global experts.

Publication

Publishing through the conference enhances the visibility of your research and connects your work with a broader academic audience.