Methodology Seminar Series

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.

Seminars are on Thursdays from 16:15- 17:45  and take place in COL 8.13 (Columbia House 8th Floor)- Please see here for a map of the LSE).

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If you would like further information on the seminars, please email

PhD students and staff across the LSE are welcome to attend.

Summer Term Seminars

The Department Seminar Series will return in Michaelmas Term 2018. Details to follow...

Please click here to see details of previous seminars...

Data Science Seminar Series

The new Social and Economic Data Science (SEDS) Research Unit, which is affiliated to the Department of Methodology is now running its own seminar series focusing on data science. These will also take place on Thursdays from 16:15 - 17:45 in COL 8.13. Forthcoming seminars are listed below:

Summer Term Seminars

Karsten Donnay

Integrating Conflict Event Data
Date: Thursday 4th May 2017
Speaker: Karsten Donnay, University of Konstanz

The growing volume of sophisticated event-level data collection, with improving geographic and temporal coverage, offers prospects for conducting novel analyses. In instances where multiple related datasets are available, researchers tend to rely on one at a time, ignoring the potential value of the multiple datasets in providing more comprehensive, precise, and valid measurement of empirical phenomena. If multiple datasets are used, integration is typically limited to manual efforts for select cases. We develop the conceptual and methodological foundations for automated, transparent and reproducible integration and disambiguation of multiple event datasets. We formally present the methodology, validate it with synthetic test data, and demonstrate its application using conflict event data for Africa, drawing on four leading sources (UCDP-GED, ACLED, SCAD, GTD). We show that whether analyses rely on one or multiple datasets can affect substantive findings with regard to key explanatory variables, thus highlighting the critical importance of systematic data integration.

Andreas Jungherr

Normalizing Digital Trace Data

Date: POSTPONED - This seminar will now be taking place in October. Exact date TBC.
Speaker:  Andreas Jungherr, University of Konstanz

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 Andreas 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, he will outline the two fallacies in greater detail then 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, he will present selected prominent studies predominantly from political communication research. Andreas 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.