Abstract
Past studies of sentiment analysis have mainly applied algorithms based on vocabulary categories and emotional characteristics to detect the emotionality of text. However, the collocation of state-changing words and emotional vocabulary affects emotions. For example, adverbs of degree strengthen emotions, and negative adverbs reverse emotions. This study investigated the weighted effect of state-changing words on emotion. The research material comprised 73 state-changing words that were collocated with four emotions: happiness, sadness, fear, and anger. A total of 84 participants participated in the vocabulary assessment. The results revealed that state-changing words could be classified into four types: intensifying, weakening, neutralizing, and reversing. In a comparison of the weighting factors among emotions, the weighting effect of the same state-changing word in the positive emotion category was particularly evident. The results could serve as a reference for follow-up studies on detecting emotions in text.
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