A Method for Detecting and Analyzing the Sentiment of Tweets Containing Conditional Sentences

Society is developing daily, and consequently, the population is more interested in public opinion. Surveys are frequently organized for detecting the attitude as well as the belief of the community in situations and their opinion about the measures or products. Users particularly express their feelings through comments posted on social networks, such as Twitter. Tweet sentiment analysis is a process that automatically detects personal information from the public emotion of the users about the events or products related to them from published tweets. Many studies have solved the sentiment analysis problem with high accuracy for the general tweets. However, these previous studies did not consider or dealt with low performance in case of tweets containing conditional sentences. In this study, we focus on solving the detection and sentiment analysis problem of a specific tweet type that includes conditional sentences. The results show that the proposed method achieves high performance in both the tasks.