The session addresses advances both in qualitative and quantitative digital methods, including challenges of big data analysis and computational social sciences.
Papers should address one of the questions below either at a more general methodological level or using a concrete example in a specific research project:
• What methodological innovations concerning digital methods can be observed? Where is the highest need for developing methodological approaches for integrating digital methods into empirical social research?
• Which social phenomena are captured adequately by digital data, which are not? Which qualitative and/or quantitative digital methods are best suited for which kind of theoretical problems?
• How can fields and populations be defined when using digital methods? What are appropriate sampling procedures? How can biases be corrected and how can results be generalized?
• What are the advantages and disadvantages of specific digital data and how can their quality be assessed? When are traditional, non-digital methods better suited than digital methods? When are digital data better suited?
• How can digital data be analyzed? When are assumptions of traditional methods of analysis violated and what are more appropriate ways of analysis?
• When, why and how should methods be mixed?
Peter GRAEFF1, Malte SCHWEIA2, Nina BAUR3, Lilli BRAUNISCH4, Peter GRAEFF1 and Malte SCHWEIA2, (1)Institute of Social Sciences, Christian-Albrechts University Kiel, Kiel, Germany(2)Universität Kiel, Germany(3)Technische Universität Berlin, Berlin, Germany(4)Technische Universität Berlin, Germany
