Hotel Reviews Analysis based on Sentiment Classification: Oman Case Study

Abstract

Advances in technology and in particular web applications that are related to customer relations management have encouraged users to voice their opinions with the rest of the world. Relevant information needs to be sorted within the large amount data that can employed by the organization to ensure optimal corrective actions. Sentimental Analysis is one such technique that is popular due to its ability to distil relevant information from opinionated text. Managing customer satisfaction and expectations are vital components that add credibility and ensures survival of the organization. It is commonly agreed that these are the strategic components enhance customer allegiance and covet retention. Hotels in particular are wary of the fact that opinions do matter for their reputation and credibility. Hence, they strive to seek feedback from their guests. In this paper, the authors aim to develop a model to classify hotel visitors feedback based on their experience. Four different supervised learning approaches were employed and tested on the collected data set. The result indicates Support Vector Machine (SVM) classifier outperformed the rest of the classifiers in term of effectiveness.