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.
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Notes
- 1.
CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing, China.
- 2.
Brackets correspond to arousal scale.
- 3.
Arousal differences are not reported in this section since the yare not significant.
- 4.
The VA values of these 2-characters units for the examples in Table 2 were annotated by three other native Chinese speakers.
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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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Liu, P., Li, M., Lu, Q., Han, B. (2018). Norms of Valence and Arousal for 2,076 Chinese 4-Character Words. In: Hasida, K., Pa, W. (eds) Computational Linguistics. PACLING 2017. Communications in Computer and Information Science, vol 781. Springer, Singapore. https://doi.org/10.1007/978-981-10-8438-6_8
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