Nebular: A sentiment classification system for the tourism business

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 Neb ular 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.

A novel deterministic approach for aspect-based opinion mining in tourism products reviews

“…In addition, there are a significant number of applications that mine sources that contain product reviews, such as the mentioned TripAdvisor and VirtualTourist (for tourism products) or Amazon and C|Net. Examples of these applications are the Lexalytics Salience Engine 4 and Nebular [27]. These applications process opinionated documents and generally offer text summaries as output, lacking other visualization methods.…”

Opinion Zoom: A Modular Tool to Explore Tourism Opinions on the Web

“…Examples of these applications are Lexalytics Salience Engine 4 and Nebular [2]. These applications process opinionated documents and generally offer text summaries as output, lacking other visualization methods.…”