HomeLREC 2020WorkshopsGAMNLPlrec2020-ws-gamnlp-01
Back to GAMNLP 2020
LREC 2020workshop

Creating a Sentiment Lexicon with Game-Specific Words for Analyzing NPC Dialogue in The Elder Scrolls V: Skyrim

Proceedings of the Workshop on Games and Natural Language Processing

DOI:10.63317/3micz7crn7dm

Abstract

A weak point of rule-based sentiment analysis systems is that the underlying sentiment lexicons are often not adapted to the domain of the text we want to analyze. We created a game-specific sentiment lexicon for video game Skyrim based on the E-ANEW word list and a dataset of Skyrim’s in-game documents. We calculated sentiment ratings for NPC dialogue using both our lexicon and E-ANEW and compared the resulting sentiment ratings to those of human raters. Both lexicons perform comparably well on our evaluation dialogues, but the game-specific extension performs slightly better on the dominance dimension for dialogue segments and the arousal dimension for full dialogues. To our knowledge, this is the first time that a sentiment analysis lexicon has been adapted to the video game domain.

Details

Paper ID
lrec2020-ws-gamnlp-01
Pages
pp. 1-9
BibKey
bergsma-etal-2020-creating
Editor
N/A
Publisher
European Language Resources Association (ELRA)
ISSN
N/A
ISBN
N/A
Workshop
Proceedings of the Workshop on Games and Natural Language Processing
Location
undefined, undefined
Date
11 May 2020 16 May 2020

Authors

  • TB

    Thérèse Bergsma

  • Jv

    Judith van Stegeren

  • MT

    Mariët Theune

Links