Cross-lingual Flames Detection in News Discussions
Josef Steinberger, Tomáš Brychcín, Tomáš Hercig, Peter Krejzl
Abstract
We introduce Flames Detector, an online system for measuring flames, i.e. strong negative feelings or emotions, insults or other verbal offences, in news commentaries across five languages. It is designed to assist journalists, public institutions or discussion moderators to detect news topics which evoke wrangles. We propose a machine learning approach to flames detection and calculate an aggregated score for a set of comment threads. The demo application shows the most flaming topics of the current period in several language variants. The search functionality gives a possibility to measure flames in any topic specified by a query. The evaluation shows that the flame detection in discussions is a difficult task, however, the application can already reveal interesting information about the actual news discussions.- Anthology ID:
- R17-1089
- Volume:
- Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017
- Month:
- September
- Year:
- 2017
- Address:
- Varna, Bulgaria
- Editors:
- Ruslan Mitkov, Galia Angelova
- Venue:
- RANLP
- SIG:
- Publisher:
- INCOMA Ltd.
- Note:
- Pages:
- 694–700
- Language:
- URL:
- https://doi.org/10.26615/978-954-452-049-6_089
- DOI:
- 10.26615/978-954-452-049-6_089
- Cite (ACL):
- Josef Steinberger, Tomáš Brychcín, Tomáš Hercig, and Peter Krejzl. 2017. Cross-lingual Flames Detection in News Discussions. In Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017, pages 694–700, Varna, Bulgaria. INCOMA Ltd..
- Cite (Informal):
- Cross-lingual Flames Detection in News Discussions (Steinberger et al., RANLP 2017)
- PDF:
- https://doi.org/10.26615/978-954-452-049-6_089