Allcott,Hunt Volney
Professor of Environmental Social Sciences, Senior Fellow at the Stanford Institute for Economic Policy Research and, Professor, by courtesy, of Economics
Social Sciences Division
Web page: http://allcott.stanford.edu
Academic Appointments
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Professor, Social Sciences Division
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Senior Fellow, Stanford Institute for Economic Policy Research (SIEPR)
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Professor (By courtesy), Economics
2024-25 Courses
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Independent Studies (4)
- Directed Reading
ECON 139D (Spr) - Directed Reading
ECON 239D (Spr) - Honors Thesis Research
ECON 199D (Spr) - Practical Training
ECON 299 (Spr)
- Directed Reading
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Prior Year Courses
2023-24 Courses
- Data Science for Environmental Business
ECON 185 (Spr) - Data Science for Environmental Business
MGTECON 340 (Spr) - Data Science for Environmental Business
PUBLPOL 185, SUSTAIN 135, SUSTAIN 235 (Spr) - Empirical Environmental Economics
ECON 177, SUSTAIN 130, SUSTAIN 230 (Aut) - Environmental Economics
ECON 250 (Aut)
2022-23 Courses
- Empirical Environmental Economics
ECON 177, SUSTAIN 130 (Spr)
- Data Science for Environmental Business
Stanford Advisees
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Doctoral Dissertation Reader (AC)
Matt Brown -
Master's Program Advisor
Maya Arengo, Francesca Malayeri, Claire Xu, Maliha Yousuf -
Doctoral Dissertation Co-Advisor (AC)
Tess Snyder -
Postdoctoral Research Mentor
Luming Chen
All Publications
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Asymmetric ideological segregation in exposure to political news on Facebook.
Science (New York, N.Y.)
2023; 381 (6656): 392-398
Abstract
Does Facebook enable ideological segregation in political news consumption? We analyzed exposure to news during the US 2020 election using aggregated data for 208 million US Facebook users. We compared the inventory of all political news that users could have seen in their feeds with the information that they saw (after algorithmic curation) and the information with which they engaged. We show that (i) ideological segregation is high and increases as we shift from potential exposure to actual exposure to engagement; (ii) there is an asymmetry between conservative and liberal audiences, with a substantial corner of the news ecosystem consumed exclusively by conservatives; and (iii) most misinformation, as identified by Meta's Third-Party Fact-Checking Program, exists within this homogeneously conservative corner, which has no equivalent on the liberal side. Sources favored by conservative audiences were more prevalent on Facebook's news ecosystem than those favored by liberals.
View details for DOI 10.1126/science.ade7138
View details for PubMedID 37499003
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How do social media feed algorithms affect attitudes and behavior in an election campaign?
Science (New York, N.Y.)
2023; 381 (6656): 398-404
Abstract
We investigated the effects of Facebook's and Instagram's feed algorithms during the 2020 US election. We assigned a sample of consenting users to reverse-chronologically-ordered feeds instead of the default algorithms. Moving users out of algorithmic feeds substantially decreased the time they spent on the platforms and their activity. The chronological feed also affected exposure to content: The amount of political and untrustworthy content they saw increased on both platforms, the amount of content classified as uncivil or containing slur words they saw decreased on Facebook, and the amount of content from moderate friends and sources with ideologically mixed audiences they saw increased on Facebook. Despite these substantial changes in users' on-platform experience, the chronological feed did not significantly alter levels of issue polarization, affective polarization, political knowledge, or other key attitudes during the 3-month study period.
View details for DOI 10.1126/science.abp9364
View details for PubMedID 37498999
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Reshares on social media amplify political news but do not detectably affect beliefs or opinions.
Science (New York, N.Y.)
2023; 381 (6656): 404-408
Abstract
We studied the effects of exposure to reshared content on Facebook during the 2020 US election by assigning a random set of consenting, US-based users to feeds that did not contain any reshares over a 3-month period. We find that removing reshared content substantially decreases the amount of political news, including content from untrustworthy sources, to which users are exposed; decreases overall clicks and reactions; and reduces partisan news clicks. Further, we observe that removing reshared content produces clear decreases in news knowledge within the sample, although there is some uncertainty about how this would generalize to all users. Contrary to expectations, the treatment does not significantly affect political polarization or any measure of individual-level political attitudes.
View details for DOI 10.1126/science.add8424
View details for PubMedID 37499012
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Like-minded sources on Facebook are prevalent but not polarizing.
Nature
2023
Abstract
Many critics raise concerns about the prevalence of 'echo chambers' on social media and their potential role in increasing political polarization. However, the lack of available data and the challenges of conducting large-scale field experiments have made it difficult to assess the scope of the problem1,2. Here we present data from 2020 for the entire population of active adult Facebook users in the USA showing that content from 'like-minded' sources constitutes the majority of what people see on the platform, although political information and news represent only a small fraction of these exposures. To evaluate a potential response to concerns about the effects of echo chambers, we conducted a multi-wave field experiment on Facebook among 23,377 users for whom we reduced exposure to content from like-minded sources during the 2020 US presidential election by about one-third. We found that the intervention increased their exposure to content from cross-cutting sources and decreased exposure to uncivil language, but had no measurable effects on eight preregistered attitudinal measures such as affective polarization, ideological extremity, candidate evaluations and belief in false claims. These precisely estimated results suggest that although exposure to content from like-minded sources on social media is common, reducing its prevalence during the 2020 US presidential election did not correspondingly reduce polarization in beliefs or attitudes.
View details for DOI 10.1038/s41586-023-06297-w
View details for PubMedID 37500978
View details for PubMedCentralID 9524832
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Digital Addiction
AMERICAN ECONOMIC REVIEW
2022; 112 (7): 2424-2463
View details for DOI 10.1257/aer.20210867
View details for Web of Science ID 000823623000010
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The Welfare Effects of Social Media
AMERICAN ECONOMIC REVIEW
2020; 110 (3): 629–76
View details for DOI 10.1257/aer.20190658
View details for Web of Science ID 000522716800001
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Polarization and Public Health: Partisan Differences in Social Distancing during the Coronavirus Pandemic.
Journal of public economics
2020: 104254
Abstract
We study partisan differences in Americans' response to the COVID-19 pandemic. Political leaders and media outlets on the right and left have sent divergent messages about the severity of the crisis, which could impact the extent to which Republicans and Democrats engage in social distancing and other efforts to reduce disease transmission. We develop a simple model of a pandemic response with heterogeneous agents that clarifies the causes and consequences of heterogeneous responses. We use location data from a large sample of smartphones to show that areas with more Republicans engaged in less social distancing, controlling for other factors including public policies, population density, and local COVID cases and deaths. We then present new survey evidence of significant gaps at the individual level between Republicans and Democrats in self-reported social distancing, beliefs about personal COVID risk, and beliefs about the future severity of the pandemic.
View details for DOI 10.1016/j.jpubeco.2020.104254
View details for PubMedID 32836504
View details for PubMedCentralID PMC7409721
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FOOD DESERTS AND THE CAUSES OF NUTRITIONAL INEQUALITY
QUARTERLY JOURNAL OF ECONOMICS
2019; 134 (4): 1793–1844
View details for DOI 10.1093/qje/qjz015
View details for Web of Science ID 000489163400003
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Trends in the diffusion of misinformation on social media
RESEARCH & POLITICS
2019; 6 (2)
View details for DOI 10.1177/2053168019848554
View details for Web of Science ID 000467602400001
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Social Media and Fake News in the 2016 Election
JOURNAL OF ECONOMIC PERSPECTIVES
2017; 31 (2): 211-235
View details for DOI 10.1257/jep.31.2.211
View details for Web of Science ID 000403753100010
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Social, Economic, and Ethical Concepts and Methods
CLIMATE CHANGE 2014: MITIGATION OF CLIMATE CHANGE
2014: 207–82
View details for Web of Science ID 000372635100007