Emotion-Based Story Event Clustering
- Authors
- 배병철
- Issue Date
- 19-Nov-2019
- Publisher
- Springer
- Citation
- Lecture Notes in Computer Science (LNCS), v.11869, no.1, pp.348 - 353
- Journal Title
- Lecture Notes in Computer Science (LNCS)
- Volume
- 11869
- Number
- 1
- Start Page
- 348
- End Page
- 353
- URI
- https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/869
- ISSN
- 0302-9743
- Abstract
- In this paper we explore how events can be represented and extracted from text stories, and describe the results from our simple experiment on extracting and clustering events. We applied k-means clustering algorithm and NLTK-VADER sentiment analyzer based on Plutchik’s 8 basic emotion model. When compared with human raters, some emotions show low accuracy while other emotion types, such as joy and sadness, show relatively high accuracy using our method.
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - School of Games > Game Software Major > 1. Journal Articles
![qrcode](https://api.qrserver.com/v1/create-qr-code/?size=55x55&data=https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/869)
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.