Cause Event Representations for Happiness and Surprise
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Summary
This paper presents a linguistic analysis of emotions by introducing some concrete linguistic rules in identifying the important elements of an emotion, which are the experiencer and the cause, in Chinese and examines the features of a cause event according to its degree of transitivity.
- Type
- article
- Published
- 2009-12-01
- Cited by
- 13
- References
- 17
- Access
- Open access
- OpenAlex
- https://openalex.org/W26349387
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:7739807
Keywords
Surprise, Happiness, Verb, Transitive relation, Event (particle physics)
References
- Alternation Across Semantic Fields : A Study of Mandarin Verbs of Emotion
- A Cognitive-based Annotation System for Emotion Computing
- Thematic proto-roles and argument selection
- Transitivity in Grammar and Discourse
- Semantics: Primes and Universals
- What's basic about basic emotions?
- Affective Events Theory: A theoretical discussion of the structure, causes and consequences of affective experiences at work.
- Emotion: Theory, Research and Experience
- The Emotions
- On the Origins of Human Emotions: A Sociological Inquiry into the Evolution of Human Affect
- On the Origins of Human Emotions: A Sociological Inquiry into the Evolution of Human Affect
- Emotions in crosslinguistic perspective
- A GENERAL PSYCHOEVOLUTIONARY THEORY OF EMOTION
Cited by
- Detecting Implicit Expressions of Sentiment in Text Based on Commonsense Knowledge
- Detecting implicit expressions of affect in text using EmotiNet and its extensions
- Methods and resources for sentiment analysis in multilingual documents of different text types
- Affect Detection from Social Contexts Using Commonsense Knowledge Representations
- Building and Exploiting EmotiNet, a Knowledge Base for Emotion Detection Based on the Appraisal Theory Model
- Detecting implicit expressions of emotion in text: A comparative analysis
- Extending the EmotiNet Knowledge Base to Improve the Automatic Detection of Implicitly Expressed Emotions from Text
- Emotion-Cause Pair Extraction Based on Structural and Semantic Heterogeneous Graph
- Examining emotions in English and translated Chinese children’s literature: a bilingual emotion detection model based on LLMs
- Examining emotions in English and translated Chinese children’s literature: a bilingual emotion detection model based on LLMs
- A Concept-level Emotion Cause Detection Model for Analyzing Microblogging Users’ Emotions
- EmotiNet: A Knowledge Base for Emotion Detection in Text Built on the Appraisal Theories
- Detecting Implicit Emotion Expressions from Text Using Ontological Resources and Lexical Learning
- Detecting Emotions in Social Affective Situations Using the EmotiNet Knowledge Base
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