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Framing Inequalities

Project Description

Aims and Central Research Question

Framing of information has been shown to be essential in how a person integrates knowledge into their existing belief system. A major component of framing involves language: how something is said. Our project focuses on identifying, understanding and modeling which parts of language (linguistic cues) trigger framing effects. Our point of departure are the ideas on framing as originally articulated by the psychologist James Druckman in the context of political science. Druckmann distinguishes between frames in thought, which essentially represent the belief system of a human individual and frames in communication, which are the bits of information conveyed to a human individual and which that individual then needs to integrate into their existing frame in thought. We combine this perspective with a new model of the belief systems and communication between individuals, using the linguistic concept of Common Ground. The project aims to develop a new Rich Theory of Framing (RichFrame), test it via a series of framing perception experiments and operationalize it to the extent that we can computationally model:
-    belief systems of individuals with respect to a given topic (e.g., gender, asylum seekers)
-    how new information is integrated into the belief system of an individual
-    how the framing of information affects the integration


Our domain of application is the framing of actual or perceived inequalities in the political arena. It has been well established that the perception and evaluation of inequality depends on the particular belief system that is being operated within (e.g. conservative vs. liberal). Despite some existing insights, we still do not know enough about how framing is used strategically by politicians and the media and which particular linguistic cues trigger which effects. This project contributes to a currently emerging field which studies political communication via linguistic and computational linguistic methodology and innovatively applies it to the study of social inequality.


This project brings together expertise from formal pragmatics, computational linguistics and political science, building on previous insights and computational methods, components of which are already available to the wider community online. Our RichFrame model will be based on the analysis of political discourse involving the framing of actual or perceived inequalities. Our data will be  taken from a variety of sources, including media texts, social media and political speech. This is to ensure a spread across different genres for robust and balanced points for comparison. Our project thus involves corpus creation and annotation. We will test our model via carefully controlled survey experiments and computational modelling.


General Linguistics, Computational Linguistics, Political Science

Starting Date

1 October 2019

Work Packages

Currently, our project focuses on the following work packages (WPs):

1. Automated Identification of Issue Frames

In this WP, we focus on newspaper articles and social media posts on the so-called "European Refugee Crisis" of 2014-2018, and aim at automatically detecting the most salient frames used by different media sources using natural language processing (NLP) / computational linguistic approaches.

2. Coinage Compounds as Linguistic Cues of Framing

We observed that newspaper articles and social media posts tend to use coinage compounds to implicitly convey biased attitudes, e.g., referring to Germany as "Merkel-Land" or referring to an intern wearing hijab as "hijab-intern". In this WP, we conduct experiments and formal pragmatic analyses to quantitatively investigate how the usage of such coinage compounds impact on readers’ perception of the sentiment of a given text. 

3. Frames of Deservingness of Refugees

Which refugees deserve or do not deserve which kind of assistance from a receiving country? With both computational and manual methods of text analysis, in this WP we examine social media data by a number of relevant politicians in Germany for frames of deservingness of refugees during the “European Refugee Crisis” of 2014-2018. 

Project Partners

Chris Reed (University of Dundee)

Chris Reed is a Senior Fellow at the Cluster of Excellence "The Politics of Inequality" at the University of Konstanz. Find more information on Chris Reed here.

Biljana Scott (DiploFoundation)

Biljana Scott teaches issues of framing to diplomats at the DiploFoundation. Her current research is on implicit communication and the ‘unsaid’ in political and diplomatic discourse. She will advise on the annotation scheme and help design stimuli testing framing effects with respect to issues of inequality. Find more information about Biljana Scott here


Further Reading

Alesina, Alberto and George-Marios Angeletos. 2005. Fairness and Redistribution. The American Economic Review 95(4):960–980.

Bartels, Larry M. 2005. Homer Gets a Tax Cut: Inequality and Public Policy in the American Mind. Perspectives on Politics 3(1):15–31.

Bartels, Larry M. 2008. Unequal Democracy: The Political Economy of the New Gilded Age. Princeton, NJ: Princeton University Press.

Buckledee, Steve. 2018. The Language of Brexit: How Britain Talked Its Way Out of the European Union. London, UK; New York, NY: Bloomsbury Academic.

Chong, Dennis and James N. Druckman. 2012. Counterframing effects. The Journal of Politics 75:1–16.

Druckman, James N. 2011. What’s it all about?: Framing in political science. In G. Keren, ed., Perspectives on Framing, pages 279–301. Taylor and Francis.

Lakoff, George. 2014. The All New Don’t Think of an Elephant! Know Your Values and Frame the Debate. White River Junction, VT: Chelsea Green Publishing.

Publications and Talks


Fliethmann, Anselm, Seibel, Verena, and Daniel Degen. 2024. Deservingness Perceptions Towards Refugees: A Gender Perspective. Journal of Immigrant and Refugee Studies. [LINK]

Yu, Qi, Fabian Schlotterbeck, Hening Wang, Naomi Reichmann, Britta Stolterfoht, Regine Eckardt and Miriam Butt. 2024. Ad Hoc Compounds for Stance Detection. Proceedings of the Joint Workshop on Multiword Expressions and Universal Dependencies (MWE-UD 2024). [PDF]

Yu, Qi. 2023. Towards a More In-Depth Detection of Political Framing. Proceedings of the 6th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature. [PDF]

Yu, Qi. 2022. "Again, Dozens of Refugees Drowned": A Computational Study of Political Framing Evoked by Presuppositions. Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL): Student Research Workshop. [PDF]

Yu, Qi, and Anselm Fliethmann. 2022. Frame Detection in German Political Discourses: How Far Can We Go without Large-Scale Manual Corpus Annotation? Journal for Language Technology and Computational Linguistics 35 (2): 15–31. [LINK]

Yu, Qi, and Anselm Fliethmann. 2021. Frame detection in German political discourses: How far can we go without large-scale manual corpus annotation? In Proceedings of 1st Workshop on Computational Linguistics for Political Text Analysis, pages 13–24. [PDF]  

Yu, Qi, and Anselm Fliethmann. 2021. Dataset: The Refugee and Migration Framing Schema (RMFS) and Refugee and Migration Framing Vocabulary (RMFV). [LINK]