Using Sentiment Analysis to Assess Customer Satisfaction in an Online Job Search Company

The Internet is a reality in people’s lives, enabling the growth of many online services companies. However, to maintain their activities and stay in the market, it’s important for these companies to worry about the quality of the provided services. In this context, it becomes important to be able to assess the client satisfaction regarding those services. The objective of this work is to propose a tool for aiding the evaluation of customer satisfaction in a Brazilian Online Job Search Company through the use of Sentiment Analysis. Sentiment Analysis, or Opinion Mining, refers to the techniques used to extract and evaluate sentiment expressed in textual data. We analyzed a database of an online job search company containing client comments collected from a service cancellation form. This database, among other parameters, has a score assigned by the client and a comment about the services. We performed the classification of the sentiment expressed in the user comments with the aid of a software written in Python, and then calculated the correlation of the sentiment score with the score assigned by the clients. The results lead to the conclusion that the use of Sentiment Analysis serves as a support tool to enrich the customer satisfaction assessment.