Sentiment Analysis of Conversational Implicature: A Computational Pragmatics Approach

The process of inferring the intention of conversational implicatures involves the interpretation of the speaker’s sentiment. However, the relationship between implicatures and sentiments has not been clear enough, and there is no research explaining the relationship between the response orientation of conversational implicature and sentiment score. Therefore, based on the dialogue snippets of conversational implicature, this paper uses automatic sentiment analysis, statistical testing and other methods to identify the statistical dependencies between implicatures and sentiments, and compare the sentiment scores of implicatures and literal meanings. The results show that the response orientation of implicature has a significant impact on the sentiment score, and its source only contains response utterance. In addition, within the response utterance, whether there is a significant difference between the sentiment scores of implicature and literal meaning is related to the selected algorithms of sentiment analysis. The sentiment lexicon-based method like Pattern cannot distinguish the sentimental difference between implicature and literal meaning, but the sentiment score obtained by the VADER-based method that considers grammatical and syntactical heuristics has significant differences in implicatures and literal meanings. Finally, the methodological implications of the experiments and results for the development of computational pragmatics are provided in this paper.