A Real-Time System for Credibility on Twitter
Adrian Iftene, Daniela Gifu, Andrei-Remus Miron, Mihai-Stefan Dudu
Abstract
Nowadays, social media credibility is a pressing issue for each of us who are living in an altered online landscape. The speed of news diffusion is striking. Given the popularity of social networks, more and more users began posting pictures, information, and news about personal life. At the same time, they started to use all this information to get informed about what their friends do or what is happening in the world, many of them arousing much suspicion. The problem we are currently experiencing is that we do not currently have an automatic method of figuring out in real-time which news or which users are credible and which are not, what is false or what is true on the Internet. The goal of this is to analyze Twitter in real-time using neural networks in order to provide us key elements about both the credibility of tweets and users who posted them. Thus, we make a real-time heatmap using information gathered from users to create overall images of the areas from which this fake news comes.- Anthology ID:
- 2020.lrec-1.757
- Volume:
- Proceedings of the Twelfth Language Resources and Evaluation Conference
- Month:
- May
- Year:
- 2020
- Address:
- Marseille, France
- Editors:
- Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 6166–6173
- Language:
- English
- URL:
- https://aclanthology.org/2020.lrec-1.757
- DOI:
- Cite (ACL):
- Adrian Iftene, Daniela Gifu, Andrei-Remus Miron, and Mihai-Stefan Dudu. 2020. A Real-Time System for Credibility on Twitter. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 6166–6173, Marseille, France. European Language Resources Association.
- Cite (Informal):
- A Real-Time System for Credibility on Twitter (Iftene et al., LREC 2020)
- PDF:
- https://preview.aclanthology.org/improve-issue-templates/2020.lrec-1.757.pdf