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
- Venue:
- GAMESandNLP
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 1–9
- Language:
- English
- URL:
- https://aclanthology.org/2020.gamnlp-1.1
- DOI:
- Cite (ACL):
- Thérèse Bergsma, Judith van Stegeren, and Mariët Theune. 2020. Creating a Sentiment Lexicon with Game-Specific Words for Analyzing NPC Dialogue in The Elder Scrolls V: Skyrim. In Workshop on Games and Natural Language Processing, pages 1–9, Marseille, France. European Language Resources Association.
- Cite (Informal):
- Creating a Sentiment Lexicon with Game-Specific Words for Analyzing NPC Dialogue in The Elder Scrolls V: Skyrim (Bergsma et al., GAMESandNLP 2020)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/2020.gamnlp-1.1.pdf