ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2003.03318
  4. Cited By
A Longitudinal Analysis of YouTube's Promotion of Conspiracy Videos

A Longitudinal Analysis of YouTube's Promotion of Conspiracy Videos

6 March 2020
Marc Faddoul
Guillaume Chaslot
Hany Farid
ArXiv (abs)PDFHTML

Papers citing "A Longitudinal Analysis of YouTube's Promotion of Conspiracy Videos"

15 / 15 papers shown
Datasets for Navigating Sensitive Topics in Recommendation Systems
Datasets for Navigating Sensitive Topics in Recommendation SystemsThe Web Conference (WWW), 2025
Amelia Kovacs
Jerry Chee
Kimia Kazemian
Sarah Dean
141
2
0
08 Sep 2025
Evaluating AI capabilities in detecting conspiracy theories on YouTube
Evaluating AI capabilities in detecting conspiracy theories on YouTube
Leonardo La Rocca
Francesco Corso
Francesco Pierri
244
0
0
29 May 2025
Uncovering Conspiratorial Narratives within Arabic Online Content
Uncovering Conspiratorial Narratives within Arabic Online Content
Djamila Mohdeb
Meriem Laifa
Zineb Guemraoui
Dalila Behih
156
0
0
18 Apr 2025
Algorithmic Behaviors Across Regions: A Geolocation Audit of YouTube Search for COVID-19 Misinformation Between the United States and South Africa
Algorithmic Behaviors Across Regions: A Geolocation Audit of YouTube Search for COVID-19 Misinformation Between the United States and South AfricaInternational Conference on Web and Social Media (ICWSM), 2024
Hayoung Jung
Prerna Juneja
Tanushree Mitra
MLAU
410
2
0
16 Sep 2024
System-2 Recommenders: Disentangling Utility and Engagement in
  Recommendation Systems via Temporal Point-Processes
System-2 Recommenders: Disentangling Utility and Engagement in Recommendation Systems via Temporal Point-Processes
Arpit Agarwal
Nicolas Usunier
A. Lazaric
Maximilian Nickel
337
8
0
29 May 2024
In the Eye of the Beholder: Robust Prediction with Causal User Modeling
In the Eye of the Beholder: Robust Prediction with Causal User ModelingNeural Information Processing Systems (NeurIPS), 2022
Amir Feder
G. Horowitz
Yoav Wald
Roi Reichart
Nir Rosenfeld
OOD
373
7
0
01 Jun 2022
Subscriptions and external links help drive resentful users to
  alternative and extremist YouTube videos
Subscriptions and external links help drive resentful users to alternative and extremist YouTube videos
Annie Y Chen
B. Nyhan
Jason Reifler
Ronald E. Robertson
Christo Wilson
208
15
0
22 Apr 2022
Reason Against the Machine: Future Directions for Mass Online
  Deliberation
Reason Against the Machine: Future Directions for Mass Online DeliberationFrontiers in Political Science (Front. Polit. Sci.), 2021
R. Shortall
A. Itten
Michiel van der Meer
P. Murukannaiah
Catholijn M. Jonker
LRM
272
37
0
27 Jul 2021
Quantifying Availability and Discovery in Recommender Systems via
  Stochastic Reachability
Quantifying Availability and Discovery in Recommender Systems via Stochastic ReachabilityInternational Conference on Machine Learning (ICML), 2021
Mihaela Curmei
Sarah Dean
Benjamin Recht
149
10
0
30 Jun 2021
Investigating Misinformation Dissemination on Social Media in Pakistan
D.W.G. Haroon
Hammad Arif
Ahmed Abdullah Tariq
Fareeda Nawaz
Dr. Ihsan Ayyub Qazi
Dr. Maryam mustafa
156
1
0
17 Jun 2021
Problematic Machine Behavior: A Systematic Literature Review of
  Algorithm Audits
Problematic Machine Behavior: A Systematic Literature Review of Algorithm Audits
Jack Bandy
MLAU
219
136
0
03 Feb 2021
Do Offline Metrics Predict Online Performance in Recommender Systems?
Do Offline Metrics Predict Online Performance in Recommender Systems?
K. Krauth
Sarah Dean
Alex Zhao
Wenshuo Guo
Mihaela Curmei
Benjamin Recht
Sai Li
OffRL
226
48
0
07 Nov 2020
Understanding YouTube Communities via Subscription-based Channel
  Embeddings
Understanding YouTube Communities via Subscription-based Channel Embeddings
Sam Clark
Anna Zaitsev
119
7
0
19 Oct 2020
Balancing Competing Objectives with Noisy Data: Score-Based Classifiers
  for Welfare-Aware Machine Learning
Balancing Competing Objectives with Noisy Data: Score-Based Classifiers for Welfare-Aware Machine LearningInternational Conference on Machine Learning (ICML), 2020
Esther Rolf
Max Simchowitz
Sarah Dean
Lydia T. Liu
Daniel Björkegren
Moritz Hardt
J. Blumenstock
272
26
0
15 Mar 2020
YouTube Recommendations and Effects on Sharing Across Online Social
  Platforms
YouTube Recommendations and Effects on Sharing Across Online Social Platforms
C. Buntain
Richard Bonneau
Jonathan Nagler
Joshua A. Tucker
CML
304
53
0
02 Mar 2020
1
Page 1 of 1