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Article ; Online: Viewing the US presidential electoral map through the lens of public health.

Hamamsy, Tymor / Danziger, Michael / Nagler, Jonathan / Bonneau, Richard

PloS one

2021 Volume 16, Issue 7, Page(s) e0254001

Abstract: Health, disease, and mortality vary greatly at the county level, and there are strong geographical trends of disease in the United States. Healthcare is and has been a top priority for voters in the U.S., and an important political issue. Consequently, ... ...

Abstract	Health, disease, and mortality vary greatly at the county level, and there are strong geographical trends of disease in the United States. Healthcare is and has been a top priority for voters in the U.S., and an important political issue. Consequently, it is important to determine what relationship voting patterns have with health, disease, and mortality, as doing so may help guide appropriate policy. We performed a comprehensive analysis of the relationship between voting patterns and over 150 different public health and wellbeing variables at the county level, comparing all states, including counties in 2016 battleground states, and counties in states that flipped from majority Democrat to majority Republican from 2012 to 2016. We also investigated county-level health trends over the last 30+ years and find statistically significant relationships between a number of health measures and the voting patterns of counties in presidential elections. Collectively, these data exhibit a strong pattern: counties that voted Republican in the 2016 election had overall worse health outcomes than those that voted Democrat. We hope that this strong relationship can guide improvements in healthcare policy legislation at the county level.
MeSH term(s)	Federal Government ; Geography, Medical ; Government Employees ; Health Expenditures/statistics & numerical data ; Health Policy ; Health Status Indicators ; Humans ; Morbidity ; Mortality ; Politics ; Public Health ; United States
Language	English
Publishing date	2021-07-21
Publishing country	United States
Document type	Comparative Study ; Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ISSN	1932-6203
ISSN (online)	1932-6203
DOI	10.1371/journal.pone.0254001
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Exposure to the Russian Internet Research Agency foreign influence campaign on Twitter in the 2016 US election and its relationship to attitudes and voting behavior.

Eady, Gregory / Paskhalis, Tom / Zilinsky, Jan / Bonneau, Richard / Nagler, Jonathan / Tucker, Joshua A

Nature communications

2023 Volume 14, Issue 1, Page(s) 62

Abstract: There is widespread concern that foreign actors are using social media to interfere in elections worldwide. Yet data have been unavailable to investigate links between exposure to foreign influence campaigns and political behavior. Using longitudinal ... ...

Abstract	There is widespread concern that foreign actors are using social media to interfere in elections worldwide. Yet data have been unavailable to investigate links between exposure to foreign influence campaigns and political behavior. Using longitudinal survey data from US respondents linked to their Twitter feeds, we quantify the relationship between exposure to the Russian foreign influence campaign and attitudes and voting behavior in the 2016 US election. We demonstrate, first, that exposure to Russian disinformation accounts was heavily concentrated: only 1% of users accounted for 70% of exposures. Second, exposure was concentrated among users who strongly identified as Republicans. Third, exposure to the Russian influence campaign was eclipsed by content from domestic news media and politicians. Finally, we find no evidence of a meaningful relationship between exposure to the Russian foreign influence campaign and changes in attitudes, polarization, or voting behavior. The results have implications for understanding the limits of election interference campaigns on social media.
MeSH term(s)	Humans ; Social Media ; Politics ; Attitude ; Internationality ; Russia
Language	English
Publishing date	2023-01-09
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-022-35576-9
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Article ; Online: Online searches to evaluate misinformation can increase its perceived veracity.

Aslett, Kevin / Sanderson, Zeve / Godel, William / Persily, Nathaniel / Nagler, Jonathan / Tucker, Joshua A

Nature

2023 Volume 625, Issue 7995, Page(s) 548–556

Abstract: Considerable scholarly attention has been paid to understanding belief in online ... ...

Abstract	Considerable scholarly attention has been paid to understanding belief in online misinformation
MeSH term(s)	Humans ; Disinformation ; Online Social Networking ; Probability ; Public Opinion ; Search Engine/statistics & numerical data ; Social Media/statistics & numerical data ; Trust
Language	English
Publishing date	2023-12-20
Publishing country	England
Document type	Journal Article
ZDB-ID	120714-3
ISSN	1476-4687 ; 0028-0836
ISSN (online)	1476-4687
ISSN	0028-0836
DOI	10.1038/s41586-023-06883-y
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Zs.A 26: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (1.OG) ab Jg. 2022: Lesesaal (EG)
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Book ; Online: Large Language Models Can Be Used to Estimate the Latent Positions of Politicians

Wu, Patrick Y. / Nagler, Jonathan / Tucker, Joshua A. / Messing, Solomon

2023

Abstract: Existing approaches to estimating politicians' latent positions along specific dimensions often fail when relevant data is limited. We leverage the embedded knowledge in generative large language models (LLMs) to address this challenge and measure ... ...

Abstract	Existing approaches to estimating politicians' latent positions along specific dimensions often fail when relevant data is limited. We leverage the embedded knowledge in generative large language models (LLMs) to address this challenge and measure lawmakers' positions along specific political or policy dimensions. We prompt an instruction/dialogue-tuned LLM to pairwise compare lawmakers and then scale the resulting graph using the Bradley-Terry model. We estimate novel measures of U.S. senators' positions on liberal-conservative ideology, gun control, and abortion. Our liberal-conservative scale, used to validate LLM-driven scaling, strongly correlates with existing measures and offsets interpretive gaps, suggesting LLMs synthesize relevant data from internet and digitized media rather than memorizing existing measures. Our gun control and abortion measures -- the first of their kind -- differ from the liberal-conservative scale in face-valid ways and predict interest group ratings and legislator votes better than ideology alone. Our findings suggest LLMs hold promise for solving complex social science measurement problems. Comment: 18 pages, 4 figures; V2: fixed graphical error on Figure 2; V3: reorganized sections, updated prose; V4: added additional scales and analysis
Keywords	Computer Science - Computers and Society ; Computer Science - Computation and Language
Publishing date	2023-03-21
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Concept-Guided Chain-of-Thought Prompting for Pairwise Comparison Scaling of Texts with Large Language Models

Wu, Patrick Y. / Nagler, Jonathan / Tucker, Joshua A. / Messing, Solomon

2023

Abstract: Existing text scaling methods often require a large corpus, struggle with short texts, or require labeled data. We develop a text scaling method that leverages the pattern recognition capabilities of generative large language models (LLMs). Specifically, ...

Abstract	Existing text scaling methods often require a large corpus, struggle with short texts, or require labeled data. We develop a text scaling method that leverages the pattern recognition capabilities of generative large language models (LLMs). Specifically, we propose concept-guided chain-of-thought (CGCoT), which uses prompts designed to summarize ideas and identify target parties in texts to generate concept-specific breakdowns, in many ways similar to guidance for human coder content analysis. CGCoT effectively shifts pairwise text comparisons from a reasoning problem to a pattern recognition problem. We then pairwise compare concept-specific breakdowns using an LLM. We use the results of these pairwise comparisons to estimate a scale using the Bradley-Terry model. We use this approach to scale affective speech on Twitter. Our measures correlate more strongly with human judgments than alternative approaches like Wordfish. Besides a small set of pilot data to develop the CGCoT prompts, our measures require no additional labeled data and produce binary predictions comparable to a RoBERTa-Large model fine-tuned on thousands of human-labeled tweets. We demonstrate how combining substantive knowledge with LLMs can create state-of-the-art measures of abstract concepts. Comment: 26 pages, 2 figures
Keywords	Computer Science - Computation and Language ; Computer Science - Computers and Society
Subject code	004
Publishing date	2023-10-18
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Testing the effects of Facebook usage in an ethnically polarized setting.

Asimovic, Nejla / Nagler, Jonathan / Bonneau, Richard / Tucker, Joshua A

Proceedings of the National Academy of Sciences of the United States of America

2021 Volume 118, Issue 25

Abstract: Despite the belief that social media is altering intergroup dynamics-bringing people closer or further alienating them from one another-the impact of social media on interethnic attitudes has yet to be rigorously evaluated, especially within areas with ... ...

Abstract	Despite the belief that social media is altering intergroup dynamics-bringing people closer or further alienating them from one another-the impact of social media on interethnic attitudes has yet to be rigorously evaluated, especially within areas with tenuous interethnic relations. We report results from a randomized controlled trial in Bosnia and Herzegovina (BiH), exploring the effects of exposure to social media during 1 wk around genocide remembrance in July 2019 on a set of interethnic attitudes of Facebook users. We find evidence that, counter to preregistered expectations, people who deactivated their Facebook profiles report lower regard for ethnic outgroups than those who remained active. Moreover, we present additional evidence suggesting that this effect is likely conditional on the level of ethnic heterogeneity of respondents' residence. We also extend the analysis to include measures of subjective well-being and knowledge of news. Here, we find that Facebook deactivation leads to suggestive improvements in subjective wellbeing and a decrease in knowledge of current events, replicating results from recent research in the United States in a very different context, thus increasing our confidence in the generalizability of these effects.
MeSH term(s)	Attitude ; Ethnicity ; Genocide ; Health ; Humans ; Intention to Treat Analysis ; Knowledge ; Social Media ; Surveys and Questionnaires
Language	English
Publishing date	2021-06-15
Publishing country	United States
Document type	Journal Article
ZDB-ID	209104-5
ISSN	1091-6490 ; 0027-8424
ISSN (online)	1091-6490
ISSN	0027-8424
DOI	10.1073/pnas.2022819118
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Zs.A 1148: Show issues

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Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (1.OG)
ab Jg. 2022: Lesesaal (EG)

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Article ; Online: Most users do not follow political elites on Twitter; those who do show overwhelming preferences for ideological congruity.

Wojcieszak, Magdalena / Casas, Andreu / Yu, Xudong / Nagler, Jonathan / Tucker, Joshua A

Science advances

2022 Volume 8, Issue 39, Page(s) eabn9418

Abstract: We offer comprehensive evidence of preferences for ideological congruity when people engage with politicians, pundits, and news organizations on social media. Using 4 years of data (2016-2019) from a random sample of 1.5 million Twitter users, we examine ...

Abstract	We offer comprehensive evidence of preferences for ideological congruity when people engage with politicians, pundits, and news organizations on social media. Using 4 years of data (2016-2019) from a random sample of 1.5 million Twitter users, we examine three behaviors studied separately to date: (i) following of in-group versus out-group elites, (ii) sharing in-group versus out-group information (retweeting), and (iii) commenting on the shared information (quote tweeting). We find that the majority of users (60%) do not follow any political elites. Those who do follow in-group elite accounts at much higher rates than out-group accounts (90 versus 10%), share information from in-group elites 13 times more frequently than from out-group elites, and often add negative comments to the shared out-group information. Conservatives are twice as likely as liberals to share in-group versus out-group content. These patterns are robust, emerge across issues and political elites, and exist regardless of users' ideological extremity.
Language	English
Publishing date	2022-09-30
Publishing country	United States
Document type	Journal Article
ZDB-ID	2810933-8
ISSN	2375-2548 ; 2375-2548
ISSN (online)	2375-2548
ISSN	2375-2548
DOI	10.1126/sciadv.abn9418
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: News credibility labels have limited average effects on news diet quality and fail to reduce misperceptions.

Aslett, Kevin / Guess, Andrew M / Bonneau, Richard / Nagler, Jonathan / Tucker, Joshua A

Science advances

2022 Volume 8, Issue 18, Page(s) eabl3844

Abstract: As the primary arena for viral misinformation shifts toward transnational threats, the search continues for scalable countermeasures compatible with principles of transparency and free expression. We conducted a randomized field experiment evaluating the ...

Abstract	As the primary arena for viral misinformation shifts toward transnational threats, the search continues for scalable countermeasures compatible with principles of transparency and free expression. We conducted a randomized field experiment evaluating the impact of source credibility labels embedded in users' social feeds and search results pages. By combining representative surveys (
Language	English
Publishing date	2022-05-06
Publishing country	United States
Document type	Journal Article
ZDB-ID	2810933-8
ISSN	2375-2548 ; 2375-2548
ISSN (online)	2375-2548
ISSN	2375-2548
DOI	10.1126/sciadv.abl3844
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Less than you think: Prevalence and predictors of fake news dissemination on Facebook.

Guess, Andrew / Nagler, Jonathan / Tucker, Joshua

Science advances

2019 Volume 5, Issue 1, Page(s) eaau4586

Abstract: So-called "fake news" has renewed concerns about the prevalence and effects of misinformation in political campaigns. Given the potential for widespread dissemination of this material, we examine the individual-level characteristics associated with ... ...

Abstract	So-called "fake news" has renewed concerns about the prevalence and effects of misinformation in political campaigns. Given the potential for widespread dissemination of this material, we examine the individual-level characteristics associated with sharing false articles during the 2016 U.S. presidential campaign. To do so, we uniquely link an original survey with respondents' sharing activity as recorded in Facebook profile data. First and foremost, we find that sharing this content was a relatively rare activity. Conservatives were more likely to share articles from fake news domains, which in 2016 were largely pro-Trump in orientation, than liberals or moderates. We also find a strong age effect, which persists after controlling for partisanship and ideology: On average, users over 65 shared nearly seven times as many articles from fake news domains as the youngest age group.
Language	English
Publishing date	2019-01-09
Publishing country	United States
Document type	News ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2810933-8
ISSN	2375-2548 ; 2375-2548
ISSN (online)	2375-2548
ISSN	2375-2548
DOI	10.1126/sciadv.aau4586
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Book ; Online: YouTube Recommendations and Effects on Sharing Across Online Social Platforms

Buntain, Cody / Bonneau, Richard / Nagler, Jonathan / Tucker, Joshua A.

2020

Abstract: In January 2019, YouTube announced it would exclude potentially harmful content from video recommendations but allow such videos to remain on the platform. While this step intends to reduce YouTube's role in propagating such content, continued ... ...

Abstract	In January 2019, YouTube announced it would exclude potentially harmful content from video recommendations but allow such videos to remain on the platform. While this step intends to reduce YouTube's role in propagating such content, continued availability of these videos in other online spaces makes it unclear whether this compromise actually reduces their spread. To assess this impact, we apply interrupted time series models to measure whether different types of YouTube sharing in Twitter and Reddit changed significantly in the eight months around YouTube's announcement. We evaluate video sharing across three curated sets of potentially harmful, anti-social content: a set of conspiracy videos that have been shown to experience reduced recommendations in YouTube, a larger set of videos posted by conspiracy-oriented channels, and a set of videos posted by alternative influence network (AIN) channels. As a control, we also evaluate effects on video sharing in a dataset of videos from mainstream news channels. Results show conspiracy-labeled and AIN videos that have evidence of YouTube's de-recommendation experience a significant decreasing trend in sharing on both Twitter and Reddit. For videos from conspiracy-oriented channels, however, we see no significant effect in Twitter but find a significant increase in the level of conspiracy-channel sharing in Reddit. For mainstream news sharing, we actually see an increase in trend on both platforms, suggesting YouTube's suppressing particular content types has a targeted effect. This work finds evidence that reducing exposure to anti-social videos within YouTube, without deletion, has potential pro-social, cross-platform effects. At the same time, increases in the level of conspiracy-channel sharing raise concerns about content producers' responses to these changes, and platform transparency is needed to evaluate these effects further.
Keywords	Computer Science - Social and Information Networks ; Computer Science - Human-Computer Interaction
Subject code	303
Publishing date	2020-03-02
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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