| Summary: | In the culture of the present emojis play an important role in written/typed communication, having a primary role of supplementing the words with emotional cues. While in different cultures emojis can be interpreted and thus used differently, a small set of emojis have clear meaning and strong sentiment polarity. In this work we study how to map natural language texts to emoji sequences, more precisely, we automatically assign emojis to movie subtitles/scripts. The pipeline of the proposed method is as follows: first the most relevant words are extracted from the movie subtitle, and then these are mapped to emojis. In order to perform the mapping, three methods are proposed: a lexical matching-based, a word embedding-based and a combined approach. To demonstrate the viability of the approach, we list some of the generated emojis for a randomly selected movie subset, showing also the deficiencies of the method in generating guessable sequences. Evaluation is performed via quizzes completed by human participants.
Received by the editors: 3 November 2021.
2010 Mathematics Subject Classification. 68T50, 68T30.
1998 CR Categories and Descriptors. I.2.7 [ARTIFICIAL INTELLIGENCE]: Natural Language Processing – Text analysis; I.2.m [ARTIFICIAL INTELLIGENCE]:Miscellaneous.
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