SemEval-2015 Task 10: Sentiment Analysis in Twitter

TL;DR

This paper details the 2015 SemEval shared task on Twitter sentiment analysis, involving multiple subtasks and extensive participation, aiming to advance understanding of sentiment prediction in social media texts.

Contribution

It introduces three new subtasks for sentiment prediction in Twitter, expanding the scope of previous shared tasks and fostering comparative evaluation.

Findings

High participation with over 40 teams each year

Successful evaluation of multiple sentiment prediction subtasks

Enhanced understanding of sentiment analysis challenges in Twitter

Abstract

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.