SemEval-2013 Task 2: Sentiment Analysis in Twitter

@article{Nakov2013SemEval2013T2,
  title={SemEval-2013 Task 2: Sentiment Analysis in Twitter},
  author={Preslav Nakov and Alan Ritter and Sara Rosenthal and Fabrizio Sebastiani and Veselin Stoyanov},
  journal={ArXiv},
  year={2013},
  volume={abs/1912.06806}
}
In recent years, sentiment analysis in social media has attracted a lot of research interest and has been used for a number of applications. Unfortunately, research has been hindered by the lack of suitable datasets, complicating the comparison between approaches. To address this issue, we have proposed SemEval-2013 Task 2: Sentiment Analysis in Twitter, which included two subtasks: A, an expression-level subtask, and B, a messagelevel subtask. We used crowdsourcing on Amazon Mechanical Turk to… Expand
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References

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The 2015 iteration of the SemEval shared task on Sentiment Analysis in Twitter was the most popular sentiment analysis shared task to date with more than 40 teams participating in each of the last three years. Expand
SemEval-2014 Task 9: Sentiment Analysis in Twitter
TLDR
The Sentiment Analysis in Twitter task is described, a continuation of the last year’s task that ran successfully as part of SemEval2013 and introduced three new test sets: regular tweets, sarcastic tweets, and LiveJournal sentences. Expand
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This report summarizes the objectives and evaluation of the SemEval 2015 task on the sentiment analysis of figurative language on Twitter (Task 11). This is the first sentiment analysis task whollyExpand
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