Exploratory Analysis of News Sentiment Using Subgroup Discovery
Anita Valmarska, Luis Adrián Cabrera-Diego, Elvys Linhares Pontes, Senja Pollak
Abstract
In this study, we present an exploratory analysis of a Slovenian news corpus, in which we investigate the association between named entities and sentiment in the news. We propose a methodology that combines Named Entity Recognition and Subgroup Discovery - a descriptive rule learning technique for identifying groups of examples that share the same class label (sentiment) and pattern (features - Named Entities). The approach is used to induce the positive and negative sentiment class rules that reveal interesting patterns related to different Slovenian and international politicians, organizations, and locations.- Anthology ID:
- 2021.bsnlp-1.7
- Volume:
- Proceedings of the 8th Workshop on Balto-Slavic Natural Language Processing
- Month:
- April
- Year:
- 2021
- Address:
- Kiyv, Ukraine
- Venue:
- BSNLP
- SIG:
- SIGSLAV
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 66–72
- Language:
- URL:
- https://aclanthology.org/2021.bsnlp-1.7
- DOI:
- Cite (ACL):
- Anita Valmarska, Luis Adrián Cabrera-Diego, Elvys Linhares Pontes, and Senja Pollak. 2021. Exploratory Analysis of News Sentiment Using Subgroup Discovery. In Proceedings of the 8th Workshop on Balto-Slavic Natural Language Processing, pages 66–72, Kiyv, Ukraine. Association for Computational Linguistics.
- Cite (Informal):
- Exploratory Analysis of News Sentiment Using Subgroup Discovery (Valmarska et al., BSNLP 2021)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/2021.bsnlp-1.7.pdf