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Sentiment Analysis: Polarity Classification of TripAdvisor's Hotel Reviews

Sentiment analysis, also known as opinion mining, is a relatively new field of study that analyses subjective information in texts using Natural Language Processing (NLP) techniques.
In a globalised marketplace, businesses and organisations depend increasingly on up-to-date information about customers’ satisfaction and needs. With the development of online platforms and social networks in the past two decades, these data have become easier to obtain. Therefore, it has become of paramount importance to be able to analyse online reviews and opinionated contents in a quick and accurate way. In order to do so, unstructured texts written in natural language must be processed by NLP systems that can perform sentiment analysis to extract subjective information.
The growing attention of researchers for this area is due to its many possible applications in several domains. In this work, we discussed the use of sentiment analysis in the tourism and hospitality industry, since facilities and organisations are keen to capture tourists’ perceptions, concerns, and opinions towards destinations and hotels. These data can be retrieved on websites such as TripAdvisor, in which tourists can share their experience by publishing their supposedly truthful reviews. Hence, they can help peers in their choices and facilities in the acknowledgment of their strength and weaknesses.
The first chapter of this work provides a theoretical background by giving an overview of the literature in sentiment analysis. The second chapter of this dissertation presents the OpeNER Project, an analysis system funded by the European Union and implemented by researchers from Italy, Spain and Holland. It performs, among other tasks, also sentiment analysis and it implements components that were trained on the touristic domain and, more precisely, on accommodation reviews. Moreover, it is available online for free through some web-services and a live demo. Finally, the third chapter focuses on the actual analysis of TripAdvisor’s hotel reviews, which was done with the OpeNER demo and aimed at evaluating the demo’s performances regarding polarity detection at word-level and document-level.

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- 1 - Introduction Sentiment analysis, also known as opinion mining, is a relatively new field of study that analyses subjective information in texts using Natural Language Processing (NLP) techniques. The growing attention of researchers for this area is due to its many possible applications in several domains. One of these domains is tourism, since tourists tend to share their ideas and experiences on travel websites, such as TripAdvisor, and their opinions can be valuable both for peers and facilities. The interest for this topic was raised by the desire to find a common ground on which Computational Linguistics and English for Specific Purposes (ESP) could interact, as they are both subjects in which research is flourishing because of their applicability in numerous contexts. Thence, Sentiment Analysis, which is a branch of Computational Linguistics, and Tourism English, which is a branch of English for Specific Purposes, were combined in this project. Therefore, this dissertation will focus on sentiment analysis in the domain of tourism. More specifically, its goal is to illustrate an analysis carried out by the author on TripAdvisor’s hotel reviews using the using the live demo of a specific computational tool. The first chapter of this work will provide a theoretical background by giving an overview of the literature in sentiment analysis. After defining opinion mining and outlining its most common uses, some terminology issues will be discussed. Moreover, some popular tasks will be looked at, namely polarity classification, which aims at determining whether a text is positive or negative and which can be performed at document-, sentence- or word-level, affective state classification, which deals with emotion recognition, and sarcasm detection, which has the objective of uncovering irony in texts. Furthermore, this first chapter will illustrate the ways in which sentiment lexicons are generated and used and it will explain the ways in which computer mediated communication can influence sentiment analysis. Finally, it will focus on the importance of review mining in the touristic domain.

Tesi di Laurea Magistrale

Facoltà: Lingue straniere per la comunicazione internazionale

Autore: Chiara Martino Contatta »

Composta da 67 pagine.

 

Questa tesi ha raggiunto 426 click dal 24/07/2017.

Disponibile in PDF, la consultazione è esclusivamente in formato digitale.