Augmenting fake content detection in online platforms: A domain adaptive transfer learning via adversarial training approach
Online platforms are experimenting with interventions such as content screening to moderate the effects of fake, biased, and incensing content. Yet, online platforms face an operational challenge in implementing machine learning algorithms for managing online content due to the labeling problem, whe...
Saved in:
Main Authors: | NG, Ka Chung, KE, Ping Fan, SO, Mike K. P., TAM, Kar Yan |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2023
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/7778 https://ink.library.smu.edu.sg/context/sis_research/article/8781/viewcontent/AugmentingFakeContentDetection_pvoa_cc_by.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
BDANN : BERT-based domain adaptation neural network for multi-modal fake news detection
by: Zhang, Tong, et al.
Published: (2020) -
Fake news and scandal
by: Cabañes, Jason, et al.
Published: (2019) -
Update: mining user-news engagement patterns for dual-target cross-domain fake news detection
by: Yang, Xuankai, et al.
Published: (2025) -
Faking politics
by: Contreras, Antonio P.
Published: (2019) -
Winning the game against fake news? Using games to inoculate adolescents and young adults in Singapore against fake news
by: Tandoc, Edson C., et al.
Published: (2024)