Andrew M. Guess

Andrew M. Guess

Assistant Professor of Politics and Public Affairs

Princeton University

Biography

Welcome! I am an assistant professor of politics and public affairs at Princeton University. I use quantitative and computational methods to study the relationship between digital media and politics.

Please see the Papers page for more information about my research, which explores questions such as:

  • To what extent do digital and social media facilitate encounters with political perspectives that differ from one’s own?
  • How prevalent is online misinformation, how commonly do people encounter it on social media, and what are its effects?
  • What is the relationship between social media and political outcomes such as polarization and trust?
  • How can social platforms improve knowledge and promote news diet quality?
  • How can researchers use survey and digital trace data to measure concepts related to digital media and politics?

I’m also a founding co-editor of the Journal of Quantitative Description: Digital Media, with Kevin Munger and Eszter Hargittai. You can read our essay introducing the journal’s philosophy and goals here.

Featured Publication

Andrew M. Guess, Neil Malhotra, Jennifer Pan, Pablo Barberá, Hunt Allcott, Taylor Brown, Adriana Crespo-Tenorio, Drew Dimmery, Deen Freelon, Matthew Gentzkow, Sandra González-Bailón, Edward Kennedy, Young Mie Kim, David Lazer, Devra Moehler, Brendan Nyhan, Carlos Velasco Rivera, Jaime Settle, Daniel Robert Thomas, Emily Thorson, Rebekah Tromble, Arjun Wilkins, Magdalena Wojcieszak, Beixian Xiong, Chad Kiewiet de Jonge, Annie Franco, Winter Mason, Natalie Jomini Stroud, Joshua A. Tucker
January 2023 Science

How do social media feed algorithms affect attitudes and behavior in an election campaign?

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.
PDF DOI

Recent Publications

Like-minded sources on Facebook are prevalent but not polarizing

Many critics raise concerns about the prevalence of ‘echo chambers’ on social media and their potential role in increasing political …
Brendan Nyhan, Jaime Settle, Emily Thorson, Magdalena Wojcieszak, Pablo Barberá, Annie Y. Chen, Hunt Allcott, Taylor Brown, Adriana Crespo-Tenorio, Drew Dimmery, Deen Freelon, Matthew Gentzkow, Sandra González-Bailón, Andrew M. Guess, Edward Kennedy, Young Mie Kim, David Lazer, Neil Malhotra, Devra Moehler, Jennifer Pan, Daniel Robert Thomas, Rebekah Tromble, Carlos Velasco Rivera, Arjun Wilkins, Beixian Xiong, Chad Kiewiet de Jonge, Annie Franco, Winter Mason, Natalie Jomini Stroud, Joshua A. Tucker
PDF DOI

Asymmetric ideological segregation in exposure to political news on Facebook

Does Facebook enable ideological segregation in political news consumption? We analyzed exposure to news during the US 2020 election …
Sandra González-Bailón, David Lazer, Pablo Barberá, Meiqing Zhang, Hunt Allcott, Taylor Brown, Adriana Crespo-Tenorio, Deen Freelon, Matthew Gentzkow, Andrew M. Guess, Shanto Iyengar, Young Mie Kim, Neil Malhotra, Devra Moehler, Brendan Nyhan, Jennifer Pan, Carlos Velasco Rivera, Jaime Settle, Emily Thorson, Rebekah Tromble, Arjun Wilkins, Magdalena Wojcieszak, Chad Kiewiet de Jonge, Annie Franco, Winter Mason, Natalie Jomini Stroud, Joshua A. Tucker
PDF DOI

Reshares on social media amplify political news but do not detectably affect beliefs or opinions

We studied the effects of exposure to reshared content on Facebook during the 2020 US election by assigning a random set of consenting, …
Andrew M. Guess, Neil Malhotra, Jennifer Pan, Pablo Barberá, Hunt Allcott, Taylor Brown, Adriana Crespo-Tenorio, Drew Dimmery, Deen Freelon, Matthew Gentzkow, Sandra González-Bailón, Edward Kennedy, Young Mie Kim, David Lazer, Devra Moehler, Brendan Nyhan, Carlos Velasco Rivera, Jaime Settle, Daniel Robert Thomas, Emily Thorson, Rebekah Tromble, Arjun Wilkins, Magdalena Wojcieszak, Beixian Xiong, Chad Kiewiet de Jonge, Annie Franco, Winter Mason, Natalie Jomini Stroud, Joshua A. Tucker
PDF DOI

Who's cheating on your survey? A detection approach with digital trace data

In this note, we provide direct evidence of cheating in online assessments of political knowledge. We combine survey responses with web …
Simon Munzert, Sebastian Ramirez-Ruiz, Pablo Barberá, Andrew M. Guess, JungHwan Yang
PDF DOI

News credibility labels have limited average effects on news diet quality and fail to reduce misperceptions

As the primary arena for viral misinformation shifts toward transnational threats, the search continues for scalable countermeasures …
Kevin Aslett, Andrew M. Guess, Richard Bonneau, Jonathan Nagler, Joshua A. Tucker
PDF DOI
See all publications

Working Papers

Analysis of Web Browsing Data: A Guide

The use of individual-level browsing data, i.e., the records of a person’s visits to online content through a desktop or mobile …
Bernhard Clemm von Hohenberg, Sebastian Stier, Ana S. Cardenal, Andrew M. Guess, Ericka Menchen-Trevino, Magdalena Wojcieszak
PDF DOI

Contact

  • aguess [at] princeton.edu