Dr. Fabienne Lind, BSc. M.Sc.
Postdoctoral Researcher in Computational Communication Science
Computational Communication Science Lab | University of Vienna
Postdoctoral Researcher in Computational Communication Science
Computational Communication Science Lab | University of Vienna
Welcome! I am a Postdoctoral Researcher at the Computational Communication Science Lab in the Department of Communication at the University of Vienna. My research program focuses on the structures and dynamics of public spheres in the context of digitalization. I am particularly interested in the topics that are discussed in digital public spheres, how they are discussed and interpreted from different perspectives, and the dynamics that characterize these communication processes.
A particular focus of my work is on global and transnational public spheres. I am interested in how public interpretations and communication processes transcend national and linguistic boundaries, what effects they have, and how socio-economic, social, and geopolitical inequalities influence them. I understand digital publics as spaces of possibility that can contribute to exchange and potentially to greater global understanding between societies.
I investigate these phenomena using both traditional methods of empirical social science research and innovative computational methods such as network analysis and AI-based computational content analysis. My research focuses on political communication, international communication, and environmental communication. In my work, I combine the analysis of empirical problems with methodological research and conceptual development, collaborating closely with colleagues from various disciplines and locations around the world.
Developing and validating automated content analysis methods for cross-national and multilingual research, including machine learning approaches and large language models.
Examining how global challenges such as migration, wars, and the climate crisis are communicated across borders by media and political actors in digital public spheres.
Investigating the emotional representation and reception of climate-related political measures in social media across European countries.
Advancing methodological and conceptual foundations of cross-national communication research with digital data and computational methods.
Analyzing migration discourses, political messages on social media, and the dynamics of political communication across national and linguistic boundaries.
Studying the influence of media information on education-related knowledge inequalities and democratic participation through meta-analyses and empirical research.
Teaching Award for excellent teaching in Communication Science, Department of Communication, University of Vienna (Winter 2023/24 & Summer 2024)
PhD Award 2023 of the Computational Methods Division of the International Communication Association for the dissertation 'Multilingual automated content analysis for comparative communication research'
ICA Journalism Studies Division for "Welcome to the most arrogant network of the world!": Journalistic homophily and its effect on public discourse on Austrian Twitter" (with Phoebe Maares & Esther Greußing)
For the article 'Content analysis by the crowd: Assessing the usability of crowdsourcing for coding latent constructs' published in Communication Methods and Measures
Top 2 Student Paper Award of the Mass Communication Division of the International Communication Association for 'The knowledge gap hypothesis: A meta-analysis'
PhD methods course focusing on advanced computational text analysis techniques. Co-taught with Petro Tolochko. Covers state-of-the-art methods in automated content analysis, machine learning, and multilingual text processing for social science research.
Research practice seminar examining climate change discourse across social media platforms. Students conduct hands-on research projects analyzing climate communication using computational methods and social media data.
Supervision of bachelor students in developing and completing their thesis projects. Topics include media coverage analysis, political communication, climate communication, and social media research. Over 40 theses supervised.
This course introduces students to the fundamentals of literature-based research in social science. Students learn how to formulate research questions, locate and evaluate relevant empirical studies, and synthesize findings into a coherent scientific report.
Fundamental methods course teaching statistical analysis for communication research. Covers descriptive statistics, hypothesis testing, regression analysis, and practical data analysis using statistical software.
Invited workshops taught at GESIS (Germany), MethodsNET Summer School, University College Dublin, LMU Munich, University of Zurich, and other institutions. Focuses on computational methods for multilingual text analysis in comparative social science research.
Dr. Fabienne Lind
Department of Communication
Kolingasse 14-16
1090 Vienna, Austria
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