Using Adversarial Learning and Biterm Topic Model for an Effective Fake News Video Detection System on Heterogeneous Topics and Short Texts
Fake news videos are being actively produced and uploaded on YouTube to attract public attention. In this paper, we propose a topic-agnostic fake news video detection model based on adversarial learning and topic modeling. The proposed model estimates the topic distribution of a video using its titl...
Main Authors: | Hyewon Choi, Youngjoong Ko |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2021-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9585513/ |
Similar Items
-
O movimento antivacina no YouTube nos tempos de pós-verdade: Educação em saúde ou desinformação?
by: Bianca Barros da Costa, et al.
Published: (2020-02-01) -
Quality and Reliability of Halitosis Videos on YouTube as a Source of Information
by: Atik Ramadhani, et al.
Published: (2021-10-01) -
Adversarial Training for Fake News Classification
by: Abdullah Tariq, et al.
Published: (2022-01-01) -
ANN: adversarial news net for robust fake news classification
by: Shiza Maham, et al.
Published: (2024-04-01) -
The impact of video series to teach English pronunciation to Spanish speakers living in United States
by: Anyi Carolina Garcia Torres, et al.
Published: (2021-12-01)