SFB 1187 ›Medien der Kooperation‹ an der Universität Siegen
Media Practice Theory – Online Discussion with Sophie Müntzel (University of Lucerne): “Facing Big Data: some challenges of large-scale textual analyses for sociologists”
Wednesday, 25 November 2020, 11:00 am -12.30 pm

Due to the restrictions because of the COVID-19 pandemic, the lecture will be held asynchronous online on Tuesday 24th November, 5.00 pm (CET). We will meet with Sophie Mützel for an online-discussion Wednesday 25th November, 11.00 am (CET). For registration and further information please contact Tobias Conradi.

 

The rise of big data indicates a “watershed moment for the social sciences”. Not only are we faced with large and multifarious types of data (e.g. texts, geo location, time stamps, entire full-text archives, pictures), often very unstructured, and stemming from all sorts of sources and phenomena, we are also challenged in our theoretical underpinnings of what constitutes the social and how we can analyze it. We are also witnessing the rise of methods that help to identify patterns and relations, and to reduce complexity. Tools and algorithms of computational linguistics, machine learning, and network analysis are challenging the traditional tool kits of social science methods, which work with representative samples, independent observations, statistical significance or analysts’ privileged positions in local settings. The talk discusses some of the challenges large-scale textual data pose to sociological analysis. In particular, it highlights challenges of data construction, algorithmic models of data analysis, and data interpretation using examples of empirical studies.


Sophie Mützel, short bio

Sophie Mützel is Professor of Sociology at the Department of Sociology, University of Lucerne, Switzerland. She teaches on the sociology of algorithms, big data and social media, as well as on metrics in journalism and the digital economy within the study program “Media and Networks”. Her research interests lie in the areas of big data and its analytics, in particular text analytics and network analysis, as well as economic and cultural sociology. She recently finished a book manuscript on “Markets from stories”. She is the PI of the Swiss federal government funded NRP75 project “Facing big data: methods and skills for a 21st century sociology”. She is also part of an interdisciplinary research group on “Mining for Meaning: The Dynamics of Public Discourse on Migration” funded by the Swedish Research Council.  

Sophie studied Political Science at UC Berkeley, Sociology at Cornell University, and finished her PhD in Sociology at Columbia University. After completing her PhD, she held a Jean Monnet Fellowship at the European University Institute, Italy; afterwards she taught and conducted research at Humboldt-University Berlin and at the WZB Berlin Social Science Center. She has been a research fellow at Harvard University and held a visiting professorship at the University of Vienna.