@inproceedings{martinc-etal-2021-embeddia,
    title = "{EMBEDDIA} hackathon report: Automatic sentiment and viewpoint analysis of {S}lovenian news corpus on the topic of {LGBTIQ}+",
    author = "Martinc, Matej  and
      Perger, Nina  and
      Pelicon, Andra{\v{z}}  and
      Ul{\v{c}}ar, Matej  and
      Vezovnik, Andreja  and
      Pollak, Senja",
    editor = "Toivonen, Hannu  and
      Boggia, Michele",
    booktitle = "Proceedings of the EACL Hackashop on News Media Content Analysis and Automated Report Generation",
    month = apr,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2021.hackashop-1.17/",
    pages = "121--126",
    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."
}