Sentiment Analysis in Tickets for IT Support

Sentiment analysis has been adopted in software engineering for problems such as software usability and sentiment of developers in open-source projects. This paper proposes a method to evaluate the sentiment contained in tickets for IT (Information Technology) support. IT tickets are broad in coverage (e.g. infrastructure, software), and involve errors, incidents, requests, etc. The main challenge is to automatically distinguish between factual information, which is intrinsically negative (e.g. error description), from the sentiment embedded in the description. Our approach is to automatically create a Domain Dictionary that contains terms with sentiment in the IT context, used to filter terms in ticket for sentiment analysis. We experiment and evaluate three approaches for calculating the polarity of terms in tickets. Our study was developed using 34,895 tickets from five organizations, from which we randomly selected 2,333 tickets to compose a Gold Standard. Our best results display an average precision and recall of 82.83% and 88.42%, which outperforms the compared sentiment analysis solutions.