SemEval-2017 Task 4: Sentiment Analysis in Twitter

Sara Rosenthal, Noura Farra, Preslav Nakov


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.
Anthology ID:
S17-2088
Volume:
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)
Month:
August
Year:
2017
Address:
Vancouver, Canada
Venue:
*SEMEVAL
SIGs:
SIGLEX | SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
502–518
Language:
URL:
https://www.aclweb.org/anthology/S17-2088
DOI:
10.18653/v1/S17-2088
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/S17-2088.pdf