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Purpose

– The purpose of this paper is to propose a method of calculating the sentiment value of a tweet based on the emoticon role.

Design/methodology/approach

– Classification of emoticon roles as four types showing “emphasis”, “assuagement”, “conversion” and “addition”, with roles determined based on the respective relations to sentiment of sentences and emoticons.

Findings

– Clustering of users of four types based on emoticon sentiment.

Originality/value

– Formalization, using regression analysis, of the relation of sentiment between sentences and emoticons in all roles.

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