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

Thérèse Bergsma, Judith van Stegeren, Mariët Theune


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.
Anthology ID:
2020.gamnlp-1.1
Volume:
Workshop on Games and Natural Language Processing
Month:
May
Year:
2020
Address:
Marseille, France
Venues:
GAMESandNLP | LREC | WS
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
1–9
Language:
English
URL:
https://www.aclweb.org/anthology/2020.gamnlp-1.1
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/2020.gamnlp-1.1.pdf