A decision support system framework to track consumer sentiments in social media

A text mining and sentimental analysis technique is used to structure online reviews and present them on a decision support system with two different dashboards to assist in decision-making and may help managers develop new insights and strategies aligned with consumers’ expectations in a much more flexible and sustainable pace.

Abstract

With the evolution of web 2.0 and social networks, customers and companies’ online interaction is growing at a fast pace, containing valuable insights about consumers’ expectations that should be monitored and explored in a day-to-day basis. However, such information is highly unstructured and difficult to analyze. There is an urgent need to set up transparent methods and processes to integrate such information in the tourism industry technological infrastructure, especially for small firms that are unable to pay for expensive services to monitor their online reputation. The current paper uses a text mining and sentimental analysis technique to structure online reviews and present them on a decision support system with two different dashboards to assist in decision-making. Such system may help managers develop new insights and strategies aligned with consumers’ expectations in a much more flexible and sustainable pace.