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Identifying and Understanding User Reactions to Deceptive and Trusted
  Social News Sources

Identifying and Understanding User Reactions to Deceptive and Trusted Social News Sources

30 May 2018
M. Glenski
Tim Weninger
Svitlana Volkova
ArXiv (abs)PDFHTML

Papers citing "Identifying and Understanding User Reactions to Deceptive and Trusted Social News Sources"

4 / 4 papers shown
Title
It's about Time: Rethinking Evaluation on Rumor Detection Benchmarks
  using Chronological Splits
It's about Time: Rethinking Evaluation on Rumor Detection Benchmarks using Chronological SplitsFindings (Findings), 2023
Yida Mu
Kalina Bontcheva
Nikolaos Aletras
121
22
0
06 Feb 2023
Identifying and Characterizing Active Citizens who Refute Misinformation
  in Social Media
Identifying and Characterizing Active Citizens who Refute Misinformation in Social MediaWeb Science Conference (WebSci), 2022
Yida Mu
Pu Niu
Nikolaos Aletras
203
12
0
21 Apr 2022
Fine-Tune Longformer for Jointly Predicting Rumor Stance and Veracity
Fine-Tune Longformer for Jointly Predicting Rumor Stance and Veracity
Anant Khandelwal
165
22
0
15 Jul 2020
Modeling Conversation Structure and Temporal Dynamics for Jointly
  Predicting Rumor Stance and Veracity
Modeling Conversation Structure and Temporal Dynamics for Jointly Predicting Rumor Stance and VeracityConference on Empirical Methods in Natural Language Processing (EMNLP), 2019
Penghui Wei
Nan Xu
Wenji Mao
161
81
0
18 Sep 2019
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