In this paper, we describe the 2015 iteration of the SemEval shared task on Sentiment Analysis in Twitter. This was the most popular sentiment analysis shared task to date with more than 40 teams participating in each of the last three years. This year's shared task competition consisted of five sentiment prediction subtasks. Two were reruns from previous years: (A) sentiment expressed by a phrase in the context of a tweet, and (B) overall sentiment of a tweet. We further included three new subtasks asking to predict (C) the sentiment towards a topic in a single tweet, (D) the overall sentiment towards a topic in a set of tweets, and (E) the degree of prior polarity of a phrase.
@article{arxiv.1912.02387,
title = {SemEval-2015 Task 10: Sentiment Analysis in Twitter},
author = {Sara Rosenthal and Saif M Mohammad and Preslav Nakov and Alan Ritter and Svetlana Kiritchenko and Veselin Stoyanov},
journal= {arXiv preprint arXiv:1912.02387},
year = {2019}
}
Comments
Sentiment analysis, sentiment towards a topic, quantification, microblog sentiment analysis; Twitter opinion mining