A regression approach to affective rating of Chinese words from ANEW

Abstract

Affective norms for the words is an important issue in textual emotion recognition application. One problem with existing research is that several studies were rated with a large number of participants, making it difficult to apply to different languages. Moreover, difference in culture across different ethnic groups makes the language/culture-specific affective norms not directly translatable to the applications using different languages. To overcome these problems, in this paper, a new approach to semi-automatic labeling of Chinese affective norms for the 1,034 words included in the affective norms for English words (ANEW) is proposed which use a rating of small number of Chinese words from ontology concept clusters with a regression-based approach for transforming the 1,034 English words' ratings to the corresponding Chinese words' ratings. The experimental result demonstrated that the proposed approach can be practically implemented and provide adequate results. © 2011 Springer-Verlag.