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Introduction:

Sentiment Analysis has gained significant attention in recent years as a valuable tool for analyzing public opinion on various topics. Public opinion research plays a crucial role in understanding the sentiments, attitudes, and preferences of the general population. Sentiment Analysis utilizes natural language processing, text analysis, and computational linguistics to identify and extract subjective information from textual data. This information is then used to gauge the sentiment of the text, whether it is positive, negative, or neutral. In this thesis, we will delve into the application of Sentiment Analysis in Public Opinion Research, exploring its methodologies, tools, challenges, and implications.

Table of Contents:

Chapter 1: Introduction
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 2: Literature Review
2.1 Overview of Sentiment Analysis
2.2 Theoretical Frameworks in Sentiment Analysis
2.3 Applications of Sentiment Analysis in Public Opinion Research
2.4 Tools and Techniques in Sentiment Analysis
2.5 Challenges in Sentiment Analysis
2.6 Sentiment Analysis in Social Media
2.7 Sentiment Analysis in Political Science
2.8 Sentiment Analysis in Marketing
2.9 Sentiment Analysis in Customer Feedback
2.10 Future Trends in Sentiment Analysis

Chapter 3: Research Methodology
3.1 Research Design
3.2 Data Collection
3.3 Data Preprocessing
3.4 Sentiment Analysis Algorithms
3.5 Evaluation Metrics
3.6 Software and Tools
3.7 Case Studies
3.8 Ethical Considerations

Chapter 4: Discussion of Findings
4.1 Analysis of Results
4.2 Comparison with Existing Studies
4.3 Implications for Public Opinion Research
4.4 Recommendations for Future Research
4.5 Case Studies Analysis
4.6 Limitations of the Study
4.7 Practical Applications
4.8 Policy Recommendations

Chapter 5: Conclusion and Summary
5.1 Summary of Findings
5.2 Conclusions
5.3 Contributions to the Field
5.4 Future Research Directions
5.5 Final Thoughts

Thesis Overview:

Sentiment Analysis has become an increasingly popular tool for analyzing public opinion, thanks to the vast amount of textual data available on the Internet. This thesis explores the application of Sentiment Analysis in Public Opinion Research, utilizing natural language processing and computational linguistics techniques to extract and analyze sentiment from textual data. The literature review covers the theoretical frameworks, applications, tools, and challenges in Sentiment Analysis, with a focus on its use in social media, political science, marketing, and customer feedback. The research methodology section outlines the design, data collection, preprocessing, algorithms, evaluation metrics, software, and case studies used in the study. The discussion of findings analyzes the results, compares them with existing studies, and provides implications, recommendations, and limitations of the study. The conclusion and summary section summarizes the findings, conclusions, contributions to the field, future research directions, and provides final thoughts on Sentiment Analysis for Public Opinion Research.

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