Social Simulation
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AI Models, Computational Methods, and Workflows for CSSH
We develop AI models and computational methods to analyse complex data, supporting research in social sciences and humanities while promoting Open Science and FAIR principles.
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AI Psychometrics and Complexity Science
We use traditional and advanced computational methods, including NLP, to study digital discourse, exploring belief updating, emotional decay, online polarization, and LLM psychometrics. Leveraging semantic embeddings, we gain insights into language structures to understand online behaviour and societal impact.
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Computational Archaeology
We are an interdisciplinary team using computational innovation to advance archaeological research through AI, HPC, remote sensing, and geospatial analysis. Our mission is to uncover insights into past societies and environments, focusing on urban development, economic networks, mobility, and agriculture.
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Computational Archival History
Our group develops tools to process and extract text from digitized historical documents in Catalan archives. Using computer vision and natural language processing, we enhance accessibility and searchability in archives, making historical records more usable.
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Cultural Heritage and Museums
We focus on leveraging advanced technologies, such as machine learning, data analytics, computer vision etc., to study, preserve, and enhance cultural heritage
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Digital Social Ecology
We study the impact of digital platforms on human-environment interactions, with a focus on sustainability, resilience, and justice. We apply our research to areas such as urban planning, biodiversity conservation, and environmental management.
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Fair Data Stewardship, Metadata Standards, Semantics, Sensitive Data
We ensure FAIR, AI-ready data for social sciences and humanities, focusing on quality, interoperability, and automation within the CSSH repository at BSC Dataverse.
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Natural Language Processing for the Humanities
We apply computational methods to study language and analyse texts, specialising in NLP techniques for text mining, data processing, and historical document transcription. Our current focus is automating medieval manuscript transcription and extracting structured data using LLMs.
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Policy analysis
Policy analysis shapes our society in many ways. Increasingly, modelling and simulation are gaining popularity to study social dynamics. These techniques provide a virtual laboratory to test what-if scenarios that can assess decision making processes.
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Science and Technology Studies
Science and Technology Studies examines how knowledge is produced, focusing on global inequalities. We analyze scientific publications, researcher mobility, collaboration, and methods to assess their societal and technological impact.
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Smart and resilient cities
We are interested in studying how to use the analysis of structured and unstructured data to address societal challenges such as energy efficiency, e-government, or public safety. More specifically, our research is related with in semantic and open data for smartcities and analysis of textual information.
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Social Media, Politics and Behavior
We explore how digital media, algorithms, and social media influence political views, engagement, and public opinion, examining the role of cross-political communication in shaping or deepening political divides.
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Urban Data Science
Cities are projected to absorb more than two-thirds of the growth in global population. Making cities inclusive, safe, resilient, and sustainable has thus become a global priority. In our team, we use data to study the interactions that occur in cities: between their residents and with their environment.
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Welfare and Equity
The Welfare and Equity Team examines the impact of policies on socio-economic mobility and well-being. They use data to identify patterns for more effective and equitable policies. Their aim is to improve outcomes for individuals and society.