A Method for Detecting and Analyzing the Sentiment of Tweets Containing Fuzzy Sentiment Phrases

Abstract

Owing to the development and dissemination of Twitter, an increasing number of users' opinions about various topics are being published on Twitter and have become a significant data source for numerous applications; one of the most popular is tweet sentiment analysis. Many researchers have tried to solve this problem with different methods. However, previous studies have only focused on sentiment analysis of general tweets without considering a divide-and-conquer strategy. Meanwhile, a large number of tweets contains fuzzy sentiment phrases. Thus, effectively solving fuzzy sentiment phrases may help to significantly improve the performance of sentiment analysis methods. In this study, we concentrate only on the detection and sentiment analysis problem of a specific tweet type that contains fuzzy sentiment phrases. The results show that the proposed method performs relatively well in both tasks.