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UMDuluth-CS8761 at SemEval-2018 Task 2: Emojis: Too many Choices?

机译:在SemEval-2018上的UMDuluth-CS8761任务2:表情符号:选择太多了吗?

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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 Fl score of 32.73% for the English data and 17.98% for the Spanish data.
机译:在本文中,我们介绍了根据文本将表情符号分配给推文的系统。每条推文最初都带有表情符号,任务提供者已将其删除。我们的任务是从推文中附带的20个表情符号中做出决定。提供了两个数据集-一个用英语,另一个用西班牙语。我们将该任务视为标准分类任务,其中将表情符号作为我们的类,并将推文作为我们的文档。我们性能最好的系统使用了词袋模型,将线性支持向量机作为其分类器。对于英语数据,我们获得32.73%的宏观Fl评分,对于西班牙语数据,我们获得了17.98%的宏观Fl评分。

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