Nebular: A sentiment classification system for the tourism business

The Nebular system is proposed to classify comments gathered from available travel social network websites into predefined aspects and further analyze comments into positive and negative sentiments to assist tourists to easily extract subjective information from travel socialnetwork websites.

Abstract

Due to the rapid growth of the tourism industry around the globe, tourists tend to find information of interesting attractions via available search engines. With the rapid growth of Web 2.0 in the past few years, tourists generally share their experiences through travel social network websites (Travel 2.0) such as TripAdvisor, VirtuaiTourist and Yahoo Travel. These websites have become major sources of information for tourists; however, due to the amount of available opinionated text, tourists are often overwhelmed with information. As a consequence, tourists find it extremely difficult to obtain any useful comments to make a decision regarding their travel destinations. The Nebular system is therefore proposed to classify comments gathered from available travel social network websites into predefined aspects and further analyze comments into positive and negative sentiments. This system aims to assist tourists to easily extract subjective information from travel social network websites and determine the attitude and the overall tonality of writers in the traveling domain. This can reduce the time required in searching for related information as well as easily support the growth of the tourism industry around the world.