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SemEval-2017 Task 4: Sentiment Analysis in Twitter

机译:SemEval-2017任务4:Twitter中的情感分析

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This paper describes the fifth year of the Sentiment Analysis in Twitter task. SemEval-2017 Task 4 continues with a rerun of the subtasks of SemEval-2016 Task 4, which include identifying the overall sentiment of the tweet, sentiment towards a topic with classification on a two-point and on a five-point ordinal scale, and quantification of the distribution of sentiment towards a topic across a number of tweets: again on a two-point and on a five-point ordinal scale. Compared to 2016, we made two changes: (i) we introduced a new language, Arabic, for all subtasks, and (ii) we made available information from the profiles of the Twitter users who posted the target tweets. The task continues to be very popular, with a total of 48 teams participating this year.
机译:本文介绍了Twitter中情感分析任务的第五年。 SemEval-2017任务4继续执行SemEval-2016任务4的子任务,其中包括确定推文的总体情感,针对主题的情感,并按两点和五点序的等级进​​行分类,以及在多个推文上量化对某个主题的情感分布:再次以两点和五点顺序进行。与2016年相比,我们进行了两项更改:(i)为所有子任务引入了一种新的语言阿拉伯语;(ii)从发布目标推文的Twitter用户的个人资料中获得了可用信息。这项任务仍然很受欢迎,今年共有48个团队参加。

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