%0 Generic %1 rosenthal2019semeval2017 %A Rosenthal, Sara %A Farra, Noura %A Nakov, Preslav %D 2019 %K semeval sentiment sentimentanalysis twitter %T SemEval-2017 Task 4: Sentiment Analysis in Twitter %U http://arxiv.org/abs/1912.00741 %X 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.

@misc{rosenthal2019semeval2017, abstract = {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.}, added-at = {2020-03-03T17:30:04.000+0100}, author = {Rosenthal, Sara and Farra, Noura and Nakov, Preslav}, biburl = {https://www.bibsonomy.org/bibtex/287b82d54dc8dfc8e8a70c8068506409b/albinzehe}, description = {SemEval-2017 Task 4: Sentiment Analysis in Twitter}, interhash = {e330939662fbb94649915fb58b5e67fc}, intrahash = {87b82d54dc8dfc8e8a70c8068506409b}, keywords = {semeval sentiment sentimentanalysis twitter}, note = {cite arxiv:1912.00741Comment: sentiment analysis, Twitter, classification, quantification, ranking, English, Arabic}, timestamp = {2020-03-03T17:30:04.000+0100}, title = {SemEval-2017 Task 4: Sentiment Analysis in Twitter}, url = {http://arxiv.org/abs/1912.00741}, year = 2019 }