Department seminar speaker


Departmental and Data Science seminar series

Termly events held by the Department of Methodology and the Social and Economic Data Science (SEDS) research unit.


Leading social scientists consider cutting-edge quantitative and qualitative methodologies, analyse the logic underpinning an array of approaches to empirical enquiry, and discuss the practicalities of carrying out research in a variety of different contexts.

All seminars take place in COL 8.13 from 16:15 - 17:45 unless otherwise stated. Drinks and nibbles will be served at the end.

Department of Methodology Seminar Series 

The Department Seminar Series will return in Michaelmas Term 2017. Details will be publicised here as they become available.

Social and Economic Data Science Seminars

Data Science seminars will return in Michaelmas Term 2017. One speaker is so far confirmed for this term.


Normalizing Digital Trace Data

Date: 19 October 2017
Speaker: Andreas Jungherr
Abstract: Over the last ten years, social scientists have found themselves confronting a massive increase in available data sources. In the debates on how to use these new data, the research potential of “digital trace data” has featured prominently. While various commentators expect digital trace data to create a “measurement revolution”, empirical work has fallen somewhat short of these grand expectations. In fact, empirical research based on digital trace data is largely limited by the prevalence of two central fallacies: First, the n=all fallacy; second, the mirror fallacy. As I will argue, these fallacies can be addressed by developing a measurement theory for the use of digital trace data. For this, researchers will have to test the consequences of variations in research designs, account for sample problems arising from digital trace data, and explicitly link signals identified in digital trace data to sophisticated conceptualizations of social phenomena. Below, I will outline the two fallacies in greater detail. Then, I will discuss their consequences with regard to three general areas in the work with digital trace data in the social sciences: digital ethnography, proxies, and hybrids. In these sections, I will present selected prominent studies predominantly from political communication research. I will close by a short assessment of the road ahead and how these fallacies might be constructively addressed by the systematic development of a measurement theory for the work with digital trace data in the social sciences.