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Introduction:

Sentiment analysis is a process of analyzing text data to determine the sentiment or opinion expressed in the text. With the rapid increase in the volume of news articles being published online, there is a growing interest in analyzing the sentiment of these articles to understand public opinion and sentiment towards various topics. Sentiment analysis of news articles can provide valuable insights for businesses, governments, and researchers to make informed decisions. This thesis aims to explore the sentiment analysis of news articles and its implications.

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
2.1 Introduction to Sentiment Analysis
2.2 Sentiment Analysis Techniques
2.3 Applications of Sentiment Analysis
2.4 Sentiment Analysis in News Articles
2.5 Challenges in Sentiment Analysis
2.6 Previous Studies on Sentiment Analysis of News Articles
2.7 Sentiment Analysis Tools and Platforms
2.8 Sentiment Analysis and Machine Learning
2.9 Sentiment Analysis and Natural Language Processing
2.10 Future Trends in Sentiment Analysis

Chapter Three: Research Methodology
3.1 Research Design
3.2 Data Collection
3.3 Data Preprocessing
3.4 Sentiment Analysis Algorithm
3.5 Implementing Sentiment Analysis
3.6 Evaluation Metrics
3.7 Data Analysis Techniques
3.8 Ethical Considerations

Chapter Four: Findings and Discussion
4.1 Overview of Data
4.2 Sentiment Analysis Results
4.3 Comparison with Existing Studies
4.4 Implications of Findings
4.5 Limitations of the Study
4.6 Future Research Directions

Chapter Five: Conclusion and Summary
5.1 Summary of Findings
5.2 Contributions of the Study
5.3 Practical Implications
5.4 Theoretical Implications
5.5 Recommendations for Future Research

Thesis Overview:

Sentiment analysis of news articles has gained significant importance in recent years due to the exponential growth of digital news platforms. This thesis aims to explore the sentiment analysis of news articles and its implications for various stakeholders. The introduction provides a background of the study, problem statement, objectives, limitations, scope, significance, structure of the thesis, and definition of terms. The literature review discusses the fundamentals of sentiment analysis, techniques, applications, challenges, previous studies, tools, and future trends. The research methodology details the research design, data collection, preprocessing, algorithm, implementation, evaluation metrics, analysis techniques, and ethical considerations. The findings and discussion chapter presents the results, implications, limitations, and future research directions. The conclusion and summary chapter offers a summary of findings, contributions, practical and theoretical implications, and recommendations for future research. This thesis aims to provide valuable insights into the sentiment analysis of news articles and contribute to the existing literature in the field.

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