Abstract
As the primary source of information dissemination, social media networks have surpassed traditional news organisations for the first time. Nonetheless, as the number of people who use social media websites grows, they become more susceptible to the spread of misinformation, making it increasingly difficult
to distinguish between real news and false news in real time. In this paper, we proposed a machine learning technique for the detection of fake comments in social networks. According to the results of the experiment, it is clear that the machine learning technique efficiently detects the fake comments.
to distinguish between real news and false news in real time. In this paper, we proposed a machine learning technique for the detection of fake comments in social networks. According to the results of the experiment, it is clear that the machine learning technique efficiently detects the fake comments.
| Original language | English |
|---|---|
| Pages (from-to) | 89-93 |
| Number of pages | 5 |
| Journal | CEUR Workshop Proceedings |
| Volume | 3080 |
| Early online date | 27 Dec 2021 |
| Publication status | Published online - 27 Dec 2021 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 9 Industry, Innovation, and Infrastructure
Keywords
- Deep Learning
- Machine learning
- Fake comments
Fingerprint
Dive into the research topics of 'A Novel Approach for Fake Comments and Reviews Detection on the Online Social Networks'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver