Fetching the paper…
Reading the bibliography…
Recommendations algorithms of social media platforms are often criticized for placing users in "rabbit holes" of (increasingly) ideologically biased content.
A theory of cognitive dissonance
Leon Festinger · 1957
Earlier work this paper cites.
A Markovian Decision Process
Richard Bellman · 1957
Earlier work this paper cites.
Imperialism: Part Two Of The Origins Of Totalitarianism
Hannah Arendt · 1968
Earlier work this paper cites.
Strong Democracy Participatory Politics for a New Age
Benjamin Barber · 1984
Earlier work this paper cites.
Democracy and its Critics
Robert Alan Dahl · 1989
Earlier work this paper cites.
Who Deliberates?: Mass Media in Modern Democracy
Benjamin I. Page · 1996
Earlier work this paper cites.
Birds of a Feather: Homophily in Social Networks
Miller McPherson, Lynn Smith-Lovin, and James M Cook · 2001
Earlier work this paper cites.
Is polarization a myth?
Alan I Abramowitz and Kyle L Saunders · 2008
Earlier work this paper cites.
Spearman Rank Correlation Coefficient
Yadolah Dodge · 2008
Earlier work this paper cites.
Feeling Validated Versus Being Correct:A Meta-Analysis of Selective Exposure to Information
William Hart, Dolores Albarracín, Alice H Eagly, Inge Brechan, Matthew J Lindberg, and Lisa Merrill · 2009
Earlier work this paper cites.
Collaborative prediction and ranking with non-random missing data
Benjamin M Marlin and Richard S Zemel · 2009
Earlier work this paper cites.
Politically Motivated Reinforcement Seeking: Reframing the Selective Exposure Debate
R Kelly Garrett · 2009
Earlier work this paper cites.
Training and testing of recommender systems on data missing not at random
Harald Steck · 2010
Earlier work this paper cites.
The impact of YouTube recommendation system on video views
Renjie Zhou, Samamon Khemmarat, and Lixin Gao · 2010
Earlier work this paper cites.
Polarization and partisan selective exposure
Natalie Jomini Stroud · 2010
Earlier work this paper cites.
The Filter Bubble: What the Internet Is Hiding from You
Eli Pariser · 2011
Earlier work this paper cites.
Political Polarization on Twitter
Michael Conover, Jacob Ratkiewicz, Matthew Francisco, Bruno Gonçalves, Filippo Menczer, and Alessandro Flammini · 2011
Earlier work this paper cites.
Ideological segregation online and offline
Matthew Gentzkow and Jesse M. Shapiro · 2011
Earlier work this paper cites.
Partisan asymmetries in online political activity
Michael D Conover, Bruno Gonçalves, Alessandro Flammini, and Filippo Menczer · 2012
Earlier work this paper cites.
Decision Theory for Discrimination-Aware Classification
Faisal Kamiran, Asim Karim, and Xiangliang Zhang · 2012
Earlier work this paper cites.
How partisan media polarize America
Matthew Levendusky · 2013
Earlier work this paper cites.
Why do partisan media polarize viewers?
Matthew S Levendusky · 2013
Earlier work this paper cites.
Playing Atari with Deep Reinforcement Learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan Wierstra, and Martin Riedmiller · 2013
Earlier work this paper cites.
Echo chamber or public sphere? predicting political orientation and measuring political homophily in twitter using big data
Elanor Colleoni, Alessandro Rozza, and Adam Arvidsson · 2014
Earlier work this paper cites.
Computer supported collective action
Aaron Shaw, Haoqi Zhang, Andrés Monroy-Hernández, Sean Munson, Benjamin Mako Hill, Elizabeth Gerber, Peter Kinnaird, and Patrick Minder · 2014
Earlier work this paper cites.
Navigating the new digital divide: Capitalizing on digital influence in retail
Kasey Lobaugh, Jeff Simpson, and Lokesh Ohri · 2015
Earlier work this paper cites.
Tweeting from left to right: Is online political communication more than an echo chamber?
Pablo Barberá, John T Jost, Jonathan Nagler, Joshua A Tucker, and Richard Bonneau · 2015
Earlier work this paper cites.
Exposure to ideologically diverse news and opinion on facebook
Eytan Bakshy, Solomon Messing, and Lada A Adamic · 2015
Earlier work this paper cites.
Birds of the same feather tweet together: Bayesian ideal point estimation using twitter data
Pablo Barberá · 2015
Earlier work this paper cites.
Tom Schaul, John Quan, Ioannis Antonoglou, and David Silver · 2015
Earlier work this paper cites.
Filter bubbles, echo chambers, and online news consumption
Seth Flaxman, Sharad Goel, and Justin M Rao · 2016
Earlier work this paper cites.
Equality of Opportunity in Supervised Learning
Moritz Hardt, Eric Price, and Nati Srebro · 2016
Earlier work this paper cites.
Deep neural networks for youtube recommendations
Paul Covington, Jay Adams, and Emre Sargin · 2016
Earlier work this paper cites.
Dueling network architectures for deep reinforcement learning
Ziyu Wang, Tom Schaul, Matteo Hessel, Hado Hasselt, Marc Lanctot, and Nando Freitas · 2016
Earlier work this paper cites.
Partisan Differences Growing on a Number of Issues. Gallup
Frank Newport and Andrew Dugan · 2017
Earlier work this paper cites.
Fairness constraints: Mechanisms for fair classification
Muhammad Bilal Zafar, Isabel Valera, Manuel Gomez Rogriguez, and Krishna P Gummadi · 2017
Earlier work this paper cites.
On Fairness and Calibration
Geoff Pleiss, Manish Raghavan, Felix Wu, Jon Kleinberg, and Kilian Q Weinberger · 2017
Earlier work this paper cites.
Scalable News Slant Measurement Using Twitter
Huyen Le, Zubair Shafiq, and Padmini Srinivasan · 2017
Earlier work this paper cites.
How algorithmic confounding in recommendation systems increases homogeneity and decreases utility
Allison Chaney, Brandon Stewart, and Barbara Engelhardt · 2018
Cited alongside, same era.
YouTube’s recommendations drive 70% of what we watch. Quartz
Ashley Rodriguez · 2018
Cited alongside, same era.
YouTube, the Great Radicalizer. The New York Times
Zeynep Tufekci · 2018
Cited alongside, same era.
Social recommendation with missing not at random data
Jiawei Chen, Can Wang, Martin Ester, Qihao Shi, Yan Feng, and Chun Chen · 2018
Cited alongside, same era.
The Deconfounded Recommender: A Causal Inference Approach to Recommendation
Yixin Wang, Dawen Liang, Laurent Charlin, and David M Blei · 2018
Cited alongside, same era.
How an ex-YouTube insider investigated its secret algorithm. The Guardian
Social Norms and Selectivity: Effects of Norms of Open-Mindedness on Content Selection and Affective Polarization
Magdalena Wojcieszak, Stephan Winter, and Xudong Yu · 2020
Later among the works it cites.
A longitudinal analysis of youtube’s promotion of conspiracy videos
Marc Faddoul, Guillaume Chaslot, and Hany Farid · 2020
Later among the works it cites.
Influence Function for Unbiased Recommendation
Jiangxing Yu, Hong Zhu, Chih-Yao Chang, Xinhua Feng, Bowen Yuan, Xiuqiang He, and Zhenhua Dong · 2020
Later among the works it cites.
A General Knowledge Distillation Framework for Counterfactual Recommendation via Uniform Data
Dugang Liu, Pengxiang Cheng, Zhenhua Dong, Xiuqiang He, Weike Pan, and Zhong Ming · 2020
Later among the works it cites.
Achieving Fairness via Post-Processing in Web-Scale Recommender Systems
Preetam Nandy, Cyrus Diciccio, Divya Venugopalan, Heloise Logan, Kinjal Basu, and Noureddine El Karoui · 2020
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Paul Lewis and Erin McCormick · 2018
Cited alongside, same era.
Ex-Employee Says YouTube’s Algorithm Favors Conspiracy Theory Videos. KQED
Sam Harnett · 2018
Cited alongside, same era.
Stabilizing Reinforcement Learning in Dynamic Environment with Application to Online Recommendation
Shi-Yong Chen, Yang Yu, Qing Da, Jun Tan, Hai-Kuan Huang, and Hai-Hong Tang · 2018
Cited alongside, same era.
Recommendations with negative feedback via pairwise deep reinforcement learning
Xiangyu Zhao, Liang Zhang, Zhuoye Ding, Long Xia, Jiliang Tang, and Dawei Yin · 2018
Cited alongside, same era.
Balanced Neighborhoods for Multi-sided Fairness in Recommendation
Robin Burke, Nasim Sonboli, and Aldo Ordonez-Gauger · 2018
Cited alongside, same era.
A Fairness-aware Hybrid Recommender System
Golnoosh Farnadi, Pigi Kouki, Spencer K Thompson, Sriram Srinivasan, and Lise Getoor · 2018
Cited alongside, same era.
Auditing Partisan Audience Bias within Google Search
Ronald E Robertson, Shan Jiang, Kenneth Joseph, Lisa Friedland, David Lazer, and Christo Wilson · 2018
Cited alongside, same era.
Later among the works it cites.
POTs: protective optimization technologies
Bogdan Kulynych, Rebekah Overdorf, Carmela Troncoso, and Seda Gürses · 2020
Later among the works it cites.
Many Americans Get News on YouTube, Where News Organizations and Independent Producers Thrive Side by Side
Galen Stocking, Patrick van Kessel, Michael Barthel, Katerina Eva Matsa, and Maya Khuzam · 2020
Later among the works it cites.
No robots, spiders, or scrapers: Legal and ethical regulation of data collection methods in social media terms of service
Casey Fiesler, Nathan Beard, and Brian C Keegan · 2020
Later among the works it cites.
Federal Judge Rules It Is Not a Crime to Violate a Website’s Terms of Service. EFF
Naomi Gilens and Jamie Williams · 2020
Later among the works it cites.
Ethnic antagonism erodes Republicans’ commitment to democracy
Larry M Bartels · 2020
Later among the works it cites.
Designing Recommender Systems to Depolarize
Jonathan Stray · 2021
Later among the works it cites.
Social Media Use in 2021. Pew Research
Brooke Auxier and Monica Anderson · 2021
Later among the works it cites.
YouTube Joins Twitter, Facebook In Taking Down Trump’s Account After Capitol Siege. NPR
Jaclyn Diaz · 2021
Later among the works it cites.
Platforms Must Pay for Their Role in the Insurrection. WIRED
Roger McNamee · 2021
Later among the works it cites.
The Role of Ideology in YouTube Recommendations
Megan A. Brown, Angela Lai, Jonathan Nagler, Joshua A. Tucker, and Richard Bonneau · 2021
Later among the works it cites.
Examining the consumption of radical content on YouTube
Homa Hosseinmardi, Amir Ghasemian, Aaron Clauset, Markus Mobius, David M Rothschild, and Duncan J Watts · 2021
Later among the works it cites.
Exposure to Alternative & Extremist Content on YouTube. Anti Defamation League
Annie Y. Chen, Brendan Nyhan, Jason Reifler, Ronald E. Robertson, and Christo Wilson · 2021
Later among the works it cites.
(almost) everything in moderation: New evidence on americans’ online media diets
Andrew M Guess · 2021
Later among the works it cites.
Shared partisanship dramatically increases social tie formation in a Twitter field experiment
Mohsen Mosleh, Cameron Martel, Dean Eckles, and David G Rand · 2021
Later among the works it cites.
No polarization from partisan news
Magdalena Wojcieszak, Sjifra de Leeuw, Ericka Menchen-Trevino, Seungsu Lee, Ke Maddie Huang-Isherwood, and Brian Weeks · 2021
Later among the works it cites.
YouTube Recommendations and Effects on Sharing Across Online Social Platforms
Cody Buntain, Richard Bonneau, Jonathan Nagler, and Joshua A. Tucker · 2021
Later among the works it cites.
An Audit of Misinformation Filter Bubbles on YouTube: Bubble Bursting and Recent Behavior Changes
Matus Tomlein, Branislav Pecher, Jakub Simko, Ivan Srba, Robert Moro, Elena Stefancova, Michal Kompan, Andrea Hrckova, Juraj Podrouzek, and Maria Bielikova · 2021
Later among the works it cites.
https://support.google.com/youtube/answer/6342839
Manage your recommendations and search results. Google · 2021
Later among the works it cites.
https://developer.twitter.com/en/docs/twitter-api
Twitter API Documentation. Twitter · 2021
Later among the works it cites.
Curation Bubbles: Domain Versus URL Level Analysis of Partisan News Sharing on Social Media
Jon Green, Stefan McCabe, Sarah Shugars, John Harrington, Hanyu Chwe, Luke Horgan, Shuyang Cao, and David Lazer · 2021
Later among the works it cites.
A Survey on Bias and Fairness in Machine Learning
Ninareh Mehrabi, Fred Morstatter, Nripsuta Saxena, Kristina Lerman, and Aram Galstyan · 2021
Later among the works it cites.
Improving Sample Efficiency in Model-Free Reinforcement Learning from Images
Denis Yarats, Amy Zhang, Ilya Kostrikov, Brandon Amos, Joelle Pineau, and Rob Fergus · 2021
Later among the works it cites.
https://www.youtube.com/howyoutubeworks/our-commitments/sharing-revenue/
How YouTube Makes Money. YouTube · 2021
Later among the works it cites.
Partisanship over security: Public narratives via Twitter on foreign interferences in the 2016 and 2020 US presidential elections
Catherine Luther, Benjamin Horne, and Xu Zhang · 2021
Later among the works it cites.
https://www.youtube.com/static?template=terms
Terms of Service. YouTube · 2021
Later among the works it cites.
Van Buren is a Victory Against Overbroad Interpretations of the CFAA, and Protects Security Researchers. EFF
Aaron Mackey and Kurt Opsahl · 2021
Later among the works it cites.
https://www.youtube.com/howyoutubeworks/our-mission/
How YouTube Works - Product Features, Responsibility, & Impact · 2021
Later among the works it cites.
Data Poisoning Attacks to Deep Learning Based Recommender Systems
Hai Huang, Jiaming Mu, Neil Zhenqiang Gong, Qi Li1, Bin Liu, and Mingwei Xu · 2021
Later among the works it cites.
Neutral bots probe political bias on social media
Wen Chen, Diogo Pacheco, Kai-Cheng Yang, and Filippo Menczer · 2021
Later among the works it cites.
HARPO: Learning to Subvert Online Behavioral Advertising
Jiang Zhang, Konstantinos Psounis, Muhammad Haroon, and Zubair Shafiq · 2022
Closest in time.
Algorithmic amplification of politics on Twitter
Ferenc Huszár, Sofia Ira Ktena, Conor O’Brien, Luca Belli, Andrew Schlaikjer, and Moritz Hardt · 2022
Closest in time.
Right-wing YouTube: a supply and demand perspective
Kevin Munger and Joseph Phillips · 2022
Closest in time.