@inproceedings{field-etal-2018-framing,
title = "Framing and Agenda-setting in {R}ussian News: a Computational Analysis of Intricate Political Strategies",
author = "Field, Anjalie and
Kliger, Doron and
Wintner, Shuly and
Pan, Jennifer and
Jurafsky, Dan and
Tsvetkov, Yulia",
editor = "Riloff, Ellen and
Chiang, David and
Hockenmaier, Julia and
Tsujii, Jun{'}ichi",
booktitle = "Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing",
month = oct # "-" # nov,
year = "2018",
address = "Brussels, Belgium",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D18-1393",
doi = "10.18653/v1/D18-1393",
pages = "3570--3580",
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 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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<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 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.</abstract>
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%0 Conference Proceedings
%T Framing and Agenda-setting in Russian News: a Computational Analysis of Intricate Political Strategies
%A Field, Anjalie
%A Kliger, Doron
%A Wintner, Shuly
%A Pan, Jennifer
%A Jurafsky, Dan
%A Tsvetkov, Yulia
%Y Riloff, Ellen
%Y Chiang, David
%Y Hockenmaier, Julia
%Y Tsujii, Jun’ichi
%S Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
%D 2018
%8 oct nov
%I Association for Computational Linguistics
%C Brussels, Belgium
%F field-etal-2018-framing
%X 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 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.
%R 10.18653/v1/D18-1393
%U https://aclanthology.org/D18-1393
%U https://doi.org/10.18653/v1/D18-1393
%P 3570-3580
Markdown (Informal)
[Framing and Agenda-setting in Russian News: a Computational Analysis of Intricate Political Strategies](https://aclanthology.org/D18-1393) (Field et al., EMNLP 2018)
ACL