This workshop is dedicated to the computational study of Social Sciences, Economics and Humanities, including all subjects like, for example, education, labour market, history, religious studies, theology, cultural heritage, and informative predictions for decision-making and behavioral-science perspectives. While digital methods and AI have been emerging topics in these fields for several decades, this workshop is not only limited to discoveries in these domains, but also dedicated to the reflections of these methods and results within the field of computer science. Thus, we are in particular interested in interdisciplinary exchange and dissemination with a clear focus on computational and AI methods.
Since there is a clear methodological overlap between these three domains and often similar algorithms and AI approaches are considered, we see this workshop as place for interdisciplinary learning, discussing a joint toolbox as a support for scholars from these field with human and context-aware agents. This workshop also comprises a symposium on research towards a trustworthy data infrastructure housing both quantitative and qualitative data.
The aim of this workshop is thus to bridge the gap between scientific domains, foster interdisciplinary exchange and discuss how research questions from other domains challenge current computer science. In particular, we are interested in communications between researchers from different fields of computer science, social sciences, economics, humanities, and practitioners from different fields.
The list of topics includes, but is not limited to:
- AI approaches for the interdisciplinary work of the social sciences, economics, and humanities: report on theoretical, methodological, experimental, and applied research.
- AI for linking data from different digital resources, including online social networks, web and data mining, Knowledge Graphs, Ontologies.
- AI methods for text mining and textual analysis, for example texts within social sciences, digital literary studies, computational stylistics and stylometry.
- Text encoding, computational linguistics, annotation guidelines, OCR for humanities, economics, and social sciences.
- Network analysis, including social and historical network analysis.
The applications of interest are included in the list below, but are not limited to:
- Labour market research and qualification, including behavioral-science perspectives.
- Education: Digital methods and systems, e-learning, adult education, etc.
- Contributions to the application of technology to culture, history, and societal issues: For example, computational text analysis, analytical and visualization, databases, etc.
- In particular, we welcome submissions which focus on a critical reflection of digital methods in the humanities, economics and social sciences within computer science.
- Linking of digital resources, a discussion of data sets, their quality and reliability, combining quantitative and qualitative data, anonymization and data protection.