EMBEDDIA hackathon report: Automatic sentiment and viewpoint analysis of Slovenian news corpus on the topic of LGBTIQ+

Matej Martinc, Nina Perger, Andraž Pelicon, Matej Ulčar, Andreja Vezovnik, Senja Pollak


Abstract
We conduct automatic sentiment and viewpoint analysis of the newly created Slovenian news corpus containing articles related to the topic of LGBTIQ+ by employing the state-of-the-art news sentiment classifier and a system for semantic change detection. The focus is on the differences in reporting between quality news media with long tradition and news media with financial and political connections to SDS, a Slovene right-wing political party. The results suggest that political affiliation of the media can affect the sentiment distribution of articles and the framing of specific LGBTIQ+ specific topics, such as same-sex marriage.
Anthology ID:
2021.hackashop-1.17
Volume:
Proceedings of the EACL Hackashop on News Media Content Analysis and Automated Report Generation
Month:
April
Year:
2021
Address:
Online
Venues:
EACL | Hackashop
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
121–126
Language:
URL:
https://aclanthology.org/2021.hackashop-1.17
DOI:
Bibkey:
Cite (ACL):
Matej Martinc, Nina Perger, Andraž Pelicon, Matej Ulčar, Andreja Vezovnik, and Senja Pollak. 2021. EMBEDDIA hackathon report: Automatic sentiment and viewpoint analysis of Slovenian news corpus on the topic of LGBTIQ+. In Proceedings of the EACL Hackashop on News Media Content Analysis and Automated Report Generation, pages 121–126, Online. Association for Computational Linguistics.
Cite (Informal):
EMBEDDIA hackathon report: Automatic sentiment and viewpoint analysis of Slovenian news corpus on the topic of LGBTIQ+ (Martinc et al., Hackashop 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.hackashop-1.17.pdf