Twitter has emerged as a major social media platform and generated great interest from
sentiment analysis researchers. Despite this attention, state-of-the-art Twitter sentiment …

The opinion seeking behavior of people for good decision making has greatly enhanced the
importance of social media as a platform for exchange of information. This trend has led to a …

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 …

Sentiment classification on Twitter has attracted increasing research in recent years. Most
existing work focuses on feature engineering according to the tweet content itself. In this …

The study of evaluation, affect, and subjectivity is a multidisciplinary enterprise, including
sociology, psychology, economics, linguistics, and computer science. A number of excellent …

It has been shown that learning distributed word representations is highly useful for Twitter
sentiment classification. Most existing models rely on a single distributed representation for …

Automatically detecting sarcasm in twitter is a challenging task because sarcasm transforms
the polarity of an apparently positive or negative utterance into its opposite. Previous work …

Understanding whether preferences are sensitive to the frame has been a major topic of
debate in the last decades. For example, several works have explored whether the dictator …

With the rapid development of the Internet, more and more users utilize health communities
(known as forums) to find health-related information, share their medical stories and …

Related research for sentiment analysis on Chinese microblog is aiming at the analysis
procedure of posts. The length of short microblog text limits feature extraction of microblog …