The 5th edition of the DSSR Conference is organized by the FutureSis Group of the Italian Statistical Society. DSSR 2025 is sponsored by the Italian Statistical Society (SIS) and will take place on February 19-21, 2025 at the Pescara campus of the “G. d’Annunzio” University of Chieti-Pescara.

The conference aims to examine the challenges and opportunities presented by the “data revolution” in social research, with a particular focus on data science, statistics, and computational sciences. The emergence of new data sources presents a significant opportunity to expand our understanding and address future challenges in a range of areas, including sustainable development, social inequalities, public health, communication, and future studies.

In a time period marked by increasingly rapid and complex social changes, social data science can provide valuable insights to navigate uncertainty and explore what the future holds. As mapping out the path forward becomes more challenging, it is essential to build compasses that can guide us through an ever-evolving landscape. Futures Studies, Computational Sciences, Statistics and Social Sciences must make joint efforts and create synergies to proactively face the future.

The objective of this event is to review the current state of social data science and to identify future directions for this field of research. It encourages contributions from the core disciplines of social data science, emphasizing the importance of integrating domain-specific knowledge to enhance insights and guide future research. The conference will place particular emphasis on applications in key social research fields, addressing both qualitative and quantitative aspects of new data sources, their origins and their integration. Additionally, it will cover ethical considerations and the training of new professionals in Social Data Science. DSSR 2025 provides a unique platform for social data scientists, traditional social scientists, researchers, futurists, professionals, and policymakers to connect and share insights.

The subject matter of the contributions encompasses the following areas (but not limited to):

• Methodological and Algorithmic Issues in Social Data Science:
  • Big data issues
  • Data Sciences libraires
  • Data Security
  • Decision Support Systems
  • Delphi-methodologies
  • Empiricism and Knowledge
  • Ensemble methods
  • Features of data quality
  • Knowledge-based methods and algorithms
  • Knowledge coding and graphs
  • Machine and Deep Learning
  • Multivariate analysis
  • Pattern recognition
  • Resampling techniques
  • Scenario Development
  • Sentiment analysis
  • Social data sources integration
  • Social simulation models
  • Strategic Foresight
  • Structural Equation Modeling
  • Symbolic data analysis
  • Textual data analysis
  • Technical solutions for ethical issues in Data Science and AI 
• Applications in Social Data Science:
  • Birth rate decline and population aging
  • Communication
  • Customer Journey
  • Data Journalism
  • Digital Humanities
  • Education in Social Data Science 
  • E-Politics
  • Ethical aspects of Data Science and AI
  • Future studies
  • Gamification and Serious Games
  • Healthcare 4.0
  • Open data for social science
  • Quality of life
  • Smart cities
  • Social inequalities
  • Social networks
  • Social Science archives
  • Social Science ontologies
  • Sustainability studies

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