The Impact of Sentiment Analysis on Social Media to Assess Customer Satisfaction: Case of Rwanda
Marius Ngaboyamahina, Sun Yi · 2019
Customer satisfaction is an essential area of the industry in this 21st century sometimes as known as the information age. However, the perception of customer expectation remains a problem in today's businesses. The internet has enabled people to spread out their thoughts through Social Media (SM) platforms, forums, news comments, and blogs. Consequently, those platforms are generating exponentially the immense amounts of data. The extraction of opinions from those big data can actively allow to rate organizations, learn the consumer needs, and adjust the business's strategies. This paper presents a concept of building a rating system, using Big Data Analytics (BDA) techniques, that apply the existing Sentiment Analysis (SA) algorithms to gain insight into reviews gathered from SM applications. The system will allow to list the various categories of services and evaluate them based on the obtained the customers' reactions. Also, this study aims to manage a large volume of information to rank the institutions and provide a practical solution for competitive, marketing analysis, and track the improvement of customer satisfaction within both the public and private sectors to boost the excellent service delivery in Rwanda.