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Norms of Valence and Arousal for 2,076 Chinese 4-Character Words

Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 781)

Abstract

This study describes an annotated dataset through psycho-linguistic annotations in controlled environment on valence and arousal for a large lexicon of 2,076 Chinese 4-character words. The purpose for the annotation is to provide affect-linked knowledge to text which can be used in affective computing using NLP techniques. Analysis to the annotated data indicates that valence and arousal fit the classical U-shaped distribution. Most importantly, the annotated results indicate that the same 2-character word that appears in different 4-character words can indeed show distinct affective meanings which implies that the affective meaning of 4-character words may not be compositional to its component words. The study on this annotated list of 4-character words not only has significance at the intersection of cognitive neuroscience and social psychology, but also has great value as a resource for affective analysis in NLP applications.

Keywords

Valence Arousal Chinese words Emotion Affective analysis 

Notes

Acknowledgement

This project is supported partially by the CAS Key Laboratory of Mental Health (No. KLMH2014ZG14), the Hong Kong Scholars Program (No. XJ2015050), the National Natural Science Foundation of China (No. 31600887), RGC Funding (Pol- yU152006/16E), and HK Polytechnic University (PolyU RTVU and CERG PolyU 15211/14E).

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of ComputingThe Hong Kong Polytechnic UniversityHong KongChina
  2. 2.CAS Key Laboratory of Mental HealthInstitute of PsychologyBeijingChina
  3. 3.Department of PsychologyUniversity of Chinese Academy of SciencesBeijingChina

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