Discourse Analysis in Social Media (DaSoM)
Project title: Discourse Analysis in Social Media (DaSoM)
Project leader for the sub-project in Munich: Prof. Dr. Christoph Neuberger
Project assistant: Dr. Ines Engelmann
Grant: Federal Ministry of Education and Research (BMBF)
Project partners of the research group:
Prof. Dr. Thorsten Quandt (University of Münster, Department of Communication)
Prof. Dr. Manfred Stede (University of Potsdam, Department of Linguistics)
Prof. Dr. Stefan Stieglitz (University of Münster, Department of Department of Information Systems)
Social media applications such as Twitter, Facebook and weblogs have broadened the possibilities of pubic communication. Traditional journalistic gatekeepers are not the central mediators of topics and opinions on the internet anymore. Now all kinds of individual and collective actors can take part in public discourse, changing the processes and structures of the public sphere. Recent events such as the Arab Spring or the rise of the Pirate Party in Germany show that topics and opinions develop in a different way on the internet than in traditional media. Simultaneously, the internet allows a higher level of transparency in research: digital texts can, to a large extent, be collected and analysed automatically.
The goal of the research group is to develop and to evaluate such automatic procedures, so that in future they can be used to answer communication science questions about online discourse. One of the most frequently used methods of communication science, quantitative content analysis, is very time-consuming and costly. This is also true for qualitative methods of discourse analysis that are used in other social sciences. In order to counter these limitations, communication-science scholars and representatives of other scientific disciplines are cooperating in this research group to contribute new methodological approaches. Our Information systems partners can gather big data from various social-media applications (data tracking), and can structure these data using automated network analysis. Our partners from the field of computational linguistics have methods to analyse sentiment and discourse quality, and will in addition further develop automated content analysis procedures based on inductive text classification. In addition complementary manual procedures will be implemented. Taken together this will allow us to analyse public discourse on the micro, meso and macro level in diverse and comparative ways.
Period of funding: 01 May 2012 to 30 April 2015
Public funds for sub-project in Munich: 224.338,80 Euro (total public funds: 801.579,60 Euro)
Prof. Dr. Christoph Neuberger
Department of Communication Science and Media Research
Phone: +49 89 2180-9424