Organizers: Research Group Quantification and Social Regulation (Weizenbaum Institute for the Networked Society) and DVPW Thematic Group “Internet and Politics. Electronic Governance”


Date: 8-9 July 2019 (lunch-to-lunch)


Conference location: WZB Berlin Social Science Center, Reichpietschufer 50, D-10785 Berlin, Germany
Responsible: Dr. Lena Ulbricht lena.ulbricht [at] wzb.eu


The conference explores political epistemologies of big data. Political epistemologies are practices by which societies construct politically relevant knowledge and the criteria by which they evaluate it. These practices and criteria may originate in scientific, political, cultural, religious, and economic contexts. They evolve over time, vary between sectors, are inherently political and therefore subject to conflict. Big data is the practice of deriving socially relevant knowledge from massive and diverse digital trace data. The rise of digital technologies in all social spheres has enabled new epistemic practices which have important political implications: Political elites see digital technologies as sources of new and better tools for learning about the citizenry, for increasing political responsiveness and for improving the effectiveness of policies.


Practices such as “big data analysis”, “web scraping”, “opinion mining”, “sentiment analysis”, “predictive analytics”, and “nowcasting” seem to be common currency in the public and academic debate about the present and future of evidence-based policy making and representative democracy. Data mining and web scraping, techniques to access information “hidden” behind the user interface of a website or device, seem to establish themselves as epistemic practices with political implications. They generate knowledge about populations and the citizenry which diverge in many ways from previous ways of “seeing” and constructing the demos. Data that is based on digital collection tools is often much more personal, it can relate different kinds of information and in many cases offer an improved predictive capability. Therefore, survey methods and traditional administrative data may lose influence on political epistemologies. To rely on big data means to rely on data sources that accumulate information without awareness of the concerned individuals. This epistemic shift can be observed in policy advice, government and administration, and political campaigning. Emerging research strands such as “computational social sciences,” “social physics,” “policy analytics”, “policy informatics”, and “policy simulations” strive for better evidence, more transparency and responsiveness in policy making and governments such as in the UK, or, as in Australia, have set up strategies of “open policy making”, “agile policy making” and “public service big data”.


Political parties and advocacy groups use digital data to address citizens and muster support in a targeted manner; public authorities try to tailor public policy to public sentiment measured-online, forecast and prevent events (as in predictive policing, preemptive security and predictive healthcare), and continuously adapt policies based on real-time monitoring. An entire industry of policy consultants and technology companies thrives on the promise related to the political power of digital data and analytics. And finally, academic research engages in digitally enhanced computational social sciences, digital methods and social physics on the basis of digital trace data, machine learning and computer simulations. The political implications of these epistemic practices have yet to be examined in detail. Indeed, the rise of digital technologies in all social spheres may alter the relations between citizens and political elites in various ways: it could improve, impoverish (or simply change) political participation, policy transparency, accountability of political elites, and decision-making.

The aim of the conference is to bring together scholars from various related disciplines working on the topic, including, but not limited to: political communication, elections and party politics, science and technology studies, political theory, history, sociology and philosophy of science, critical data studies and computational social sciences. These fields of research have addressed various aspects related to political epistemologies in the digital age – but there have been only few opportunities to relate them, to compare similar practices in different fields (for example in public policy and in political campaigning) and to examine the broader picture in order to generate theories about the political epistemologies of big data, algorithms and artificial intelligence. Contributions can be both, conceptual or empirical.


The conference is interested in research concerning the following questions and similar topics:

  • What are the political epistemologies underlying the use of big data and related phenomena such as algorithms, machine learning and artificial intelligence in political contexts?

  • Which scientific, political, social and economic practices make use of digital data and methods? How do these practices construct knowledge which is deemed as politically relevant? By which (rhetoric/procedural/technical) means do these practices and the actors involved substantiate their claims to political relevance?

  • What insights can we gain from the computational social sciences in relation to traditional social science methods when it comes to political behavior, public opinion, policy making etc.?

  • How are digitally mediated political epistemologies related to other political epistemologies? How are they embedded in institutional practices and values?

  • Which interpretive conflicts do we witness with regard to the knowledge produced and legitimized by digital technologies; which are its major challengers? In which ways do epistemic practices based on big data, compared to other epistemic practices, influence the chances for challenging political knowledge claims?

  • How can we place political epistemologies in a historical or cultural perspective?

  • What are the implications of digitally mediated political epistemologies for evidence-based policy making and for representative democracy? Which conceptions of participation, representation and good governance are embedded in the related practices? How do big data-related epistemic practices reconfigure democratic concepts? Do we witness a new form of technocracy?

  • How should democratic societies shape and regulate big-data-based epistemic practices? Which contributions can we expect from algorithmic accountability, data protection and research ethics?

The conference will provide academic reflections to current public debates about the state of democracy in the digital age, considering that in 2019 various elections take place in German speaking countries, at the level of the European Parliament and within the German federal states of Bremen, Hamburg, Saxony, Brandenburg and Thuringia, as well as in Austria and Switzerland (regional and federal level). The keynote will be held by professor Daniel Kreiss, the author of a seminal book about the use of data-related practices in political campaigning (“Prototype Politics” 2016). The conference will also include artistic interventions and a lab.


The conference will offer childcare, will be video-recorded, and held in English. If the funding application is successful, the travel costs of paper presenters will be covered. The organizers plan on following up the conference with a publication project.

Abstracts should make explicit on which theories, methods and, if applicable, empirical material the paper is based. Please send your abstract of 300-500 words until 24 February 2019 to the following address: demosscraping-weizenbaum [at] wzb.eu


Preliminary program structure
8 July 2019
14.00 Welcome address
14.15 Keynote by professor Daniel Kreiss + discussion
15.30 Coffee
16.00 Paper presentations
17.30 Lab and art exhibition
18.30 Reception
9 July 2019
9.00 Paper presentations
10.30 Coffee
11.00 Paper presentations
12.30 Paper presentations or panel discussion
14.00 Ending