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**Introduction**

In recent years, the proliferation of online hotel reviews has provided a valuable resource for both travelers seeking information and hotels wanting to assess customer satisfaction. Sentiment analysis, a subfield of natural language processing (NLP), has been widely used to automatically extract and analyze sentiments expressed in text data. By utilizing deep learning techniques, such as neural networks, sentiment analysis can provide valuable insights into customer opinions and preferences.

**1.1 Introduction**

**1.2 Background of Study**

**1.3 Problem Statement**

**1.4 Objective of Study**

**1.5 Limitation of Study**

**1.6 Scope of Study**

**1.7 Significance of Study**

**1.8 Structure of the Thesis**

**1.9 Definition of Terms**

**Chapter Two: Literature Review**

– Overview of Sentiment Analysis
– Applications of Sentiment Analysis in the Hospitality Industry
– Techniques for Sentiment Analysis
– Natural Language Processing
– Deep Learning in Sentiment Analysis

**Chapter Three: Research Methodology**

– Data Collection and Preprocessing
– Feature Extraction
– Model Selection
– Evaluation Metrics
– Training and Testing
– Data Analysis Techniques
– Ethical Considerations
– Limitations of Research Methodology

**Chapter Four: Discussion of Findings**

– Analysis of Results
– Comparison with Existing Literature
– Implications for the Hospitality Industry
– Future Research Directions

**Chapter Five: Conclusion and Summary**

– Summary of Findings
– Contributions to the Field
– Practical Implications
– Recommendations for Future Research

**Thesis Overview**

The aim of this thesis is to explore the use of natural language processing and deep learning techniques in sentiment analysis of hotel reviews. The study will focus on extracting sentiment from textual data to gain insights into customer opinions and preferences within the hospitality industry. The thesis will consist of a detailed literature review, research methodology, discussion of findings, and conclusion with the aim of providing valuable insights for both researchers and industry professionals. Sentiment analysis has the potential to revolutionize the way hotels assess customer satisfaction and make informed business decisions based on customer feedback. By leveraging the power of deep learning and NLP, this study seeks to contribute to the growing body of knowledge in sentiment analysis and its applications in the hospitality industry.

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