About IDeaS

The Interpretative Data Science (IDeaS) Group is an emerging working group focused on interpretive approaches to big data modeling and theorizing in the social sciences. IDeaS is collaborative and informally structured. Its members are trying to push the boundaries of research in interpretative data science by combining quantitative and qualitative methodologies and emergent and more formalistic theorizing in the rendering process: i.e., in curating big quant and qual data, rendering varieties of models and outputs, and theorizing artifacts and relationships among them.

Distinctively, we aim to draw together three interrelated topics that are more normally studied in separate scholarly communities:

• The reflexive and theoretically informed use of new data analytic techniques in the social sciences that leverage sophisticated algorithms such as topic modeling, natural language processing, and other forms of machine learning.
• The everyday work of data analysts in organizations – how they construct knowledge practices, and the epistemic infrastructures of organizations; both as an interesting ethnographic and qualitative topic in its own right, and as a means of encouraging our own reflexivity.
• The societal, social, and cultural transformations attending the rise of data and analytics including changing forms and interpretations of privacy and governmentality – to which social scientists should be able to speak.