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Emotion-based story event clustering
- Authors
- Yu H.-Y.[Yu H.-Y.]; Park S.[Park S.]; Cheong Y.-G.[Cheong Y.-G.]; Kim M.-H.[Kim M.-H.]; Bae B.-C.[Bae B.-C.]
- Issue Date
- 2019
- Publisher
- Springer
- Keywords
- Event clustering; Event extraction; Event representation
- Citation
- Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v.11869 LNCS, pp.348 - 353
- Indexed
- SCOPUS
- Volume
- 11869 LNCS
- Start Page
- 348
- End Page
- 353
- 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. © Springer Nature Switzerland AG 2019.
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Related Researcher
- CHEONG, YUN GYUNG
- Computing and Informatics