This paper describes the results of the first shared task on Multilingual Emoji Prediction, organized as part of SemEval 2018. Given the text of a tweet, the task consists of predicting the most likely emoji to be used along such tweet. Two subtasks were proposed, one for English and one for Spanish, and participants were allowed to submit a system run to one or both subtasks. In total, 49 teams participated in the English subtask and 22 teams submitted a system run to the Spanish subtask. Evaluation was carried out emoji-wise, and the final ranking was based on macro F-Score. Data and further information about this task can be found at https://competitions.codalab.org/competitions/17344.

SemEval 2018 Task 2: Multilingual Emoji Prediction

Basile, Valerio;Patti, Viviana;
2018-01-01

Abstract

This paper describes the results of the first shared task on Multilingual Emoji Prediction, organized as part of SemEval 2018. Given the text of a tweet, the task consists of predicting the most likely emoji to be used along such tweet. Two subtasks were proposed, one for English and one for Spanish, and participants were allowed to submit a system run to one or both subtasks. In total, 49 teams participated in the English subtask and 22 teams submitted a system run to the Spanish subtask. Evaluation was carried out emoji-wise, and the final ranking was based on macro F-Score. Data and further information about this task can be found at https://competitions.codalab.org/competitions/17344.
12th International Workshop on Semantic Evaluation (SemEval 2018)
New Orleans, Louisiana
2018
Proceedings of the 12th International Workshop on Semantic Evaluation (SemEval 2018)
Association for Computational Linguistics
24
33
http://aclweb.org/anthology/S18-1003
Multilingual Emoji Prediction, Evaluation, Emoji semantics
Barbieri, Francesco; Camacho-Collados, Jose; Ronzano, Francesco; Espinosa Anke, Luis; Ballesteros, Miguel; Basile, Valerio; Patti, Viviana; Saggion, Horacio
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1682124
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