MEmoFC: introducing the Multilingual Emotional Football Corpus

Nadine Braun*, Chris van der Lee, Lorenzo Gatti, Martijn Goudbeek, Emiel Krahmer

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

This paper introduces a new corpus of paired football match reports, the Multilingual Emotional Football Corpus, (MEmoFC), which has been manually collected from English, German, and Dutch websites of individual football clubs to investigate the way different emotional states (e.g. happiness for winning and disappointment for losing) are realized in written language. In addition to the reports, it also contains the statistics for the selected matches. MEmoFC is a corpus consisting of comparable subcorpora since the authors of the texts report on the same event from two different perspectives—the winner’s and the loser’s side, and from an arguably more neutral perspective in tied matches. We demonstrate how the corpus can be used to investigate the influence of affect on the reports through different approaches and illustrate how game outcome influences (1) references to the own team and the opponent, and (2) the use of positive and negative emotion terms in the different languages. The MEmoFC corpus, together with the analyzed aspects of emotional language will open up new approaches for targeted automatic generation of texts.
Original languageEnglish
Number of pages42
JournalLanguage resources and evaluation
DOIs
Publication statusE-pub ahead of print/First online - 16 Oct 2020

Keywords

  • UT-Hybrid-D
  • Affect
  • Emotion
  • Multilingual corpus
  • Comparable corpora
  • Natural language generation
  • Sports
  • Reportage

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