Framing and Agenda-setting in Russian News: A computational analysis of intricate political strategies

Anjalie Field; Doron Kliger; Shuly Wintner; Jennifer Pan; Dan Jurafsky; Yulia Tsvetkov

Framing and Agenda-setting in Russian News: A computational analysis of intricate political strategies

Anjalie Field, Doron Kliger, Shuly Wintner, Jennifer Pan, Dan Jurafsky, Yulia Tsvetkov

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Amidst growing concern over media manipulation, NLP attention has focused on overt strategies like censorship and “fake news”. Here, we draw on two concepts from the political science literature to explore subtler strategies for government media manipulation: agenda-setting (selecting what topics to cover) and framing (deciding how topics are covered). We analyze 13 years (100K articles) of the Russian newspaper Izvestia and identify a strategy of distraction: articles mention the U.S. more frequently in the month directly following an economic downturn in Russia. We introduce embedding-based methods for cross-lingually projecting English frames to Russian, and discover that these articles emphasize U.S. moral failings and threats to the U.S. Our work offers new ways to identify subtle media manipulation strategies at the intersection of agenda-setting and framing.

Original language	English
Title of host publication	Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018
Editors	Ellen Riloff, David Chiang, Julia Hockenmaier, Jun'ichi Tsujii
Publisher	Association for Computational Linguistics
Pages	3570-3580
Number of pages	11
ISBN (Electronic)	9781948087841
State	Published - 2020
Event	2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018 - Brussels, Belgium Duration: 31 Oct 2018 → 4 Nov 2018

Publication series

Name	Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018

Conference

Conference	2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018
Country/Territory	Belgium
City	Brussels
Period	31/10/18 → 4/11/18

Bibliographical note

Funding Information:
We gratefully acknowledge our helpful reviewers and annotators and Ethan Fast for providing the NYT corpus. This research was supported by Grant No. 2017699 from the United States-Israel Binational Science Foundation (BSF), by Grant No. 1813153 from the United States National Science Foundation (NSF), and by the Stanford Cyber Initiative. Further, this material is based upon work supported by the NSF Graduate Research Fellowship Program under Grant No. DGE1745016. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF.

Publisher Copyright:
© 2018 Association for Computational Linguistics

ASJC Scopus subject areas

Computational Theory and Mathematics
Computer Science Applications
Information Systems

Cite this

Field, A., Kliger, D., Wintner, S., Pan, J., Jurafsky, D., & Tsvetkov, Y. (2020). Framing and Agenda-setting in Russian News: A computational analysis of intricate political strategies. In E. Riloff, D. Chiang, J. Hockenmaier, & J. Tsujii (Eds.), Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018 (pp. 3570-3580). (Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018). Association for Computational Linguistics.

Field, Anjalie ; Kliger, Doron ; Wintner, Shuly et al. / Framing and Agenda-setting in Russian News : A computational analysis of intricate political strategies. Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018. editor / Ellen Riloff ; David Chiang ; Julia Hockenmaier ; Jun'ichi Tsujii. Association for Computational Linguistics, 2020. pp. 3570-3580 (Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018).

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abstract = "Amidst growing concern over media manipulation, NLP attention has focused on overt strategies like censorship and “fake news”. Here, we draw on two concepts from the political science literature to explore subtler strategies for government media manipulation: agenda-setting (selecting what topics to cover) and framing (deciding how topics are covered). We analyze 13 years (100K articles) of the Russian newspaper Izvestia and identify a strategy of distraction: articles mention the U.S. more frequently in the month directly following an economic downturn in Russia. We introduce embedding-based methods for cross-lingually projecting English frames to Russian, and discover that these articles emphasize U.S. moral failings and threats to the U.S. Our work offers new ways to identify subtle media manipulation strategies at the intersection of agenda-setting and framing.",

author = "Anjalie Field and Doron Kliger and Shuly Wintner and Jennifer Pan and Dan Jurafsky and Yulia Tsvetkov",

note = "Funding Information: We gratefully acknowledge our helpful reviewers and annotators and Ethan Fast for providing the NYT corpus. This research was supported by Grant No. 2017699 from the United States-Israel Binational Science Foundation (BSF), by Grant No. 1813153 from the United States National Science Foundation (NSF), and by the Stanford Cyber Initiative. Further, this material is based upon work supported by the NSF Graduate Research Fellowship Program under Grant No. DGE1745016. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF. Publisher Copyright: {\textcopyright} 2018 Association for Computational Linguistics; 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018 ; Conference date: 31-10-2018 Through 04-11-2018",

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Field, A, Kliger, D , Wintner, S, Pan, J, Jurafsky, D & Tsvetkov, Y 2020, Framing and Agenda-setting in Russian News: A computational analysis of intricate political strategies. in E Riloff, D Chiang, J Hockenmaier & J Tsujii (eds), Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018. Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018, Association for Computational Linguistics, pp. 3570-3580, 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018, Brussels, Belgium, 31/10/18.

Framing and Agenda-setting in Russian News: A computational analysis of intricate political strategies. / Field, Anjalie; Kliger, Doron ; Wintner, Shuly et al.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018. ed. / Ellen Riloff; David Chiang; Julia Hockenmaier; Jun'ichi Tsujii. Association for Computational Linguistics, 2020. p. 3570-3580 (Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Pan, Jennifer

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N1 - Funding Information: We gratefully acknowledge our helpful reviewers and annotators and Ethan Fast for providing the NYT corpus. This research was supported by Grant No. 2017699 from the United States-Israel Binational Science Foundation (BSF), by Grant No. 1813153 from the United States National Science Foundation (NSF), and by the Stanford Cyber Initiative. Further, this material is based upon work supported by the NSF Graduate Research Fellowship Program under Grant No. DGE1745016. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF. Publisher Copyright: © 2018 Association for Computational Linguistics

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AB - Amidst growing concern over media manipulation, NLP attention has focused on overt strategies like censorship and “fake news”. Here, we draw on two concepts from the political science literature to explore subtler strategies for government media manipulation: agenda-setting (selecting what topics to cover) and framing (deciding how topics are covered). We analyze 13 years (100K articles) of the Russian newspaper Izvestia and identify a strategy of distraction: articles mention the U.S. more frequently in the month directly following an economic downturn in Russia. We introduce embedding-based methods for cross-lingually projecting English frames to Russian, and discover that these articles emphasize U.S. moral failings and threats to the U.S. Our work offers new ways to identify subtle media manipulation strategies at the intersection of agenda-setting and framing.

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BT - Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018

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Field A, Kliger D , Wintner S, Pan J, Jurafsky D, Tsvetkov Y. Framing and Agenda-setting in Russian News: A computational analysis of intricate political strategies. In Riloff E, Chiang D, Hockenmaier J, Tsujii J, editors, Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018. Association for Computational Linguistics. 2020. p. 3570-3580. (Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018).

Framing and Agenda-setting in Russian News: A computational analysis of intricate political strategies

Abstract

Publication series

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Bibliographical note

ASJC Scopus subject areas

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