Stance detection in online discussions
Peter Krejzl, Barbora Hourov\'a, Josef Steinberger

TL;DR
This paper presents a stance detection system that classifies online comments as in favor or against a target, adapting a maximum entropy classifier from English tweets to Czech news comments.
Contribution
It introduces an adaptation of a stance detection system from English to Czech, utilizing surface, sentiment, and domain-specific features with a maximum entropy classifier.
Findings
Effective adaptation to Czech news comments
Utilizes diverse feature types for stance detection
Demonstrates cross-lingual applicability of the approach
Abstract
This paper describes our system created to detect stance in online discussions. The goal is to identify whether the author of a comment is in favor of the given target or against. Our approach is based on a maximum entropy classifier, which uses surface-level, sentiment and domain-specific features. The system was originally developed to detect stance in English tweets. We adapted it to process Czech news commentaries.
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Taxonomy
TopicsSentiment Analysis and Opinion Mining · Advanced Text Analysis Techniques · Complex Network Analysis Techniques
