SemEval-2013 Task 2: Sentiment Analysis in Twitter
作者： Preslav Nakov , Zornitsa Kozareva , Sara Rosenthal , Veselin Stoyanov , Alan Ritter
DOI:
关键词: SemEval 、 World Wide Web 、 Computer science 、 Research community 、 Social media 、 Task (project management) 、 Artificial intelligence 、 Short Message Service 、 Sentiment analysis 、 Information retrieval 、 Crowdsourcing
摘要: In recent years, sentiment analysis in social media has attracted a lot of research interest and been used for number applications. Unfortunately, hindered by the lack suitable datasets, complicating comparison between approaches. To address this issue, we have proposed SemEval-2013 Task 2: Sentiment Analysis Twitter, which included two subtasks: A, an expression-level subtask, B, messagelevel subtask. We crowdsourcing on Amazon Mechanical Turk to label large Twitter training dataset along with additional test sets SMS messages both subtasks. All datasets evaluation are released community. The task significant total 149 submissions from 44 teams. bestperforming team achieved F1 88.9% 69% subtasks A respectively.
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