Emojis have been frequently used to express users’ sentiments, emotions, and feelings in text-based communication. We presented a simple and efficient method for automatically constructing an emoji sentiment lexicon with arbitrary sentiment categories. The proposed method extracts sentiment words from WordNet-Affect and calculates the co-occurrence frequency between the sentiment words and each emoji. Based on the ratio of the number of occurrences of each emoji among the sentiment categories, each emoji is assigned a multidimensional vector whose elements indicate the strength of the corresponding sentiment. In experiments conducted on a collection of tweets, we showed a high correlation between the conventional lexicon and our lexicon for three sentiment categories. We also showed the results for a new lexicon constructed with additional sentiment categories.


File 1 (3 classes) File 2 (5 classes)


If you use our lexicons, please refer to the following paper.

M. Kimura and M. Katsurai, “Automatic Construction of an Emoji Sentiment Lexicon,” Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017, pp. 1033–1036, 2017.