Cross-lingual Flames Detection in News Discussions
Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017 (2017)
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
however, the application can already reveal interesting information about the
actual news discussions.