@inproceedings{beaulieu-asamoah-owusu-2018-umduluth,
title = "{UMD}uluth-{CS}8761 at {S}em{E}val-2018 Task 2: Emojis: Too many Choices?",
author = "Beaulieu, Jonathan and
Asamoah Owusu, Dennis",
editor = "Apidianaki, Marianna and
Mohammad, Saif M. and
May, Jonathan and
Shutova, Ekaterina and
Bethard, Steven and
Carpuat, Marine",
booktitle = "Proceedings of the 12th International Workshop on Semantic Evaluation",
month = jun,
year = "2018",
address = "New Orleans, Louisiana",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/S18-1061",
doi = "10.18653/v1/S18-1061",
pages = "400--404",
abstract = "In this paper, we present our system for assigning an emoji to a tweet based on the text. Each tweet was originally posted with an emoji which the task providers removed. Our task was to decide out of 20 emojis, which originally came with the tweet. Two datasets were provided - one in English and the other in Spanish. We treated the task as a standard classification task with the emojis as our classes and the tweets as our documents. Our best performing system used a Bag of Words model with a Linear Support Vector Machine as its{'} classifier. We achieved a macro F1 score of 32.73{\%} for the English data and 17.98{\%} for the Spanish data.",
}
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<abstract>In this paper, we present our system for assigning an emoji to a tweet based on the text. Each tweet was originally posted with an emoji which the task providers removed. Our task was to decide out of 20 emojis, which originally came with the tweet. Two datasets were provided - one in English and the other in Spanish. We treated the task as a standard classification task with the emojis as our classes and the tweets as our documents. Our best performing system used a Bag of Words model with a Linear Support Vector Machine as its’ classifier. We achieved a macro F1 score of 32.73% for the English data and 17.98% for the Spanish data.</abstract>
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%0 Conference Proceedings
%T UMDuluth-CS8761 at SemEval-2018 Task 2: Emojis: Too many Choices?
%A Beaulieu, Jonathan
%A Asamoah Owusu, Dennis
%Y Apidianaki, Marianna
%Y Mohammad, Saif M.
%Y May, Jonathan
%Y Shutova, Ekaterina
%Y Bethard, Steven
%Y Carpuat, Marine
%S Proceedings of the 12th International Workshop on Semantic Evaluation
%D 2018
%8 June
%I Association for Computational Linguistics
%C New Orleans, Louisiana
%F beaulieu-asamoah-owusu-2018-umduluth
%X In this paper, we present our system for assigning an emoji to a tweet based on the text. Each tweet was originally posted with an emoji which the task providers removed. Our task was to decide out of 20 emojis, which originally came with the tweet. Two datasets were provided - one in English and the other in Spanish. We treated the task as a standard classification task with the emojis as our classes and the tweets as our documents. Our best performing system used a Bag of Words model with a Linear Support Vector Machine as its’ classifier. We achieved a macro F1 score of 32.73% for the English data and 17.98% for the Spanish data.
%R 10.18653/v1/S18-1061
%U https://aclanthology.org/S18-1061
%U https://doi.org/10.18653/v1/S18-1061
%P 400-404
Markdown (Informal)
[UMDuluth-CS8761 at SemEval-2018 Task 2: Emojis: Too many Choices?](https://aclanthology.org/S18-1061) (Beaulieu & Asamoah Owusu, SemEval 2018)
ACL