SemEval-2016 Task 4: Sentiment Analysis in Twitter
Preslav Nakov, Alan Ritter, Sara Rosenthal, Fabrizio Sebastiani, Veselin Stoyanov · 2016
This paper discusses the fourth year of the "Sentiment Analysis in Twitter Task".SemEval-2016 Task 4 comprises five subtasks, three of which represent a significant departure from previous editions.The first two subtasks are reruns from prior years and ask to predict the overall sentiment, and the sentiment towards a topic in a tweet.The three new subtasks focus on two variants of the basic "sentiment classification in Twitter" task.The first variant adopts a five-point scale, which confers an ordinal character to the classification task.The second variant focuses on the correct estimation of the prevalence of each class of interest, a task which has been called quantification in the supervised learning literature.The task continues to be very popular, attracting a total of 43 teams.