Challenge: Amidst growing concern over media manipulation, NLP studies focus on overt strategies like censorship and “fake news”.
Approach: They propose to use two concepts from political science literature to identify subtler media manipulation strategies . they propose to apply embedding-based methods to cross-lingually project English frames to Russian .
Outcome: The proposed techniques can be applied to 13 years of the Russian newspaper Izvestia and show that they highlight U.S. moral failings and threats to the U.s.

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Investigating Independence vs. Control: Agenda-Setting in Russian News Coverage on Social Media (2022.lrec-1)

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Challenge: a major challenge in the media industry has always been its targeted manipulation, says a new study . agenda-setting is a well-known phenomenon in political science . authors explore the relationship between economic indicators and mentions of foreign geopolitical entities .
Approach: They investigate agenda-setting in the Russian social media landscape . they explore the relation between economic indicators and mentions of foreign geopolitical entities .
Outcome: The authors examine the relationship between economic indicators and mentions of foreign geopolitical entities, as well as of Russia itself.
Challenges and Opportunities in Information Manipulation Detection: An Examination of Wartime Russian Media (2022.findings-emnlp)

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Challenge: Information manipulation campaigns rely on textbased news and social media content, and NLP can be a valuable tool in combating them.
Approach: They propose to use a dataset to examine the use of NLP in public opinion manipulation campaigns in the 2022 Russia-Ukraine war.
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Narratives at Conflict: Computational Analysis of News Framing in Multilingual Disinformation Campaigns (2024.acl-srw)

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Challenge: Existing methods for multilingual framing differ from those used in English-speaking world . framers often use loaded vocabularies to create political images or favor a particular point of view .
Approach: They use eight years of Russian-backed disinformation campaigns to examine framing . they find that disinformation campaign consistently favors specific framers .
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Computational Analysis of Political Texts: Bridging Research Efforts Across Communities (P19-4)

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Challenge: Political scientists have developed and adopted natural language processing (NLP) methods to exploit text as an additional source of data in their analyses.
Approach: This tutorial aims to provide a gentle introduction to methods and tasks related to computational analysis of political texts from both communities.
Outcome: The main goal of this tutorial is to bring the two research communities closer to each other and contribute to faster and more significant developments in this interdisciplinary area.
Framing in the Presence of Supporting Data: A Case Study in U.S. Economic News (2024.acl-long)

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Challenge: a lack of objective measures to evaluate editorial choices makes research difficult . a computational framework is proposed to analyze newsworthy topics with objective measures .
Approach: They propose a computational framework to analyze editorial choices in newsworthy topics . they focus on the economy because economic indicators provide a relatively easy way to determine selection and framing .
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Uncovering Agendas: A Novel French & English Dataset for Agenda Detection on Social Media (2024.lrec-main)

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Challenge: a social media analysis of online influence campaigns can reveal the sources of agenda setting . annotated data is limited or nonexistent, but there are methods to detect agenda control .
Approach: They propose a method for detecting instances of agenda control through social media . they use a modest corpus of tweets centered on the 2022 french presidential election .
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Analyzing Polarization in Social Media: Method and Application to Tweets on 21 Mass Shootings (N19-1)

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Challenge: a new framework for studying political polarization in social media is needed to understand how group divisions manifest in language.
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Multi-Modal Framing Analysis of News (2025.emnlp-main)

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Challenge: Automated frame analysis of political communication has been limited by the use of predefined frames and the visual contexts in which they appear.
Approach: They propose a method for doing multi-modal, multi-label framing analysis at scale using large (vision-) language models.
Outcome: The proposed method provides a more complete picture for understanding media bias.
“Again, Dozens of Refugees Drowned”: A Computational Study of Political Framing Evoked by Presuppositions (2022.naacl-srw)

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Challenge: Earlier studies on issue framing have focused heavily on shallow classification of issue framers, while framerical cues remain neglected.
Approach: They take presupposition-triggering adverbs such as ‘again’ as a study case and examine how different German newspapers use them to covertly evoke different attitudinal subtexts.
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A Survey of Computational Framing Analysis Approaches (2022.emnlp-main)

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Challenge: Existing computational methods for framing analysis are limited . a lack of a comprehensive understanding of framability is limiting the research .
Approach: They propose to combine existing approaches to analyze large-scale datasets using computational methods.
Outcome: The proposed methods will help scholars better understand how frames are being explored computationally, the authors argue .

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