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
Editors:
Bogdan Babych, Olga Kanishcheva, Preslav Nakov, Jakub Piskorski, Lidia Pivovarova, Vasyl Starko, Josef Steinberger, Roman Yangarber, Michał Marcińczuk, Senja Pollak, Pavel Přibáň, Marko Robnik-Šikonja
Venue:
BSNLP
SIG:
SIGSLAV
Publisher:
Association for Computational Linguistics
Note:
Pages:
66–72
Language:
URL:
https://aclanthology.org/2021.bsnlp-1.7
DOI:
Bibkey:
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)
Copy Citation:
PDF:
https://aclanthology.org/2021.bsnlp-1.7.pdf