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Table of Contents

Chapter 1: Introduction
1.1 Background of the Study
1.2 Research Problem
1.3 Research Questions
1.4 Objectives of the Study
1.5 Significance of the Study
1.6 Limitation of Study
1.7 Scope of Study

Chapter 2: Literature Review
2.1 Introduction to Data Analytics
2.2 Social Network Analysis
2.3 Data Mining Techniques for Social Network Analysis
2.4 Applications of Data Analytics in Social Network Analysis
2.5 Current Trends and Future Directions in Data Analytics for Social Network Analysis

Chapter 3: Research Methodology
3.1 Research Design
3.2 Data Collection Methods
3.3 Data Analysis Techniques
3.4 Sampling Techniques
3.5 Ethical Considerations

Chapter 4: Discussion of Findings
4.1 Data Analysis Results
4.2 Interpretation of Results
4.3 Comparison with Existing Literature
4.4 Implications of Findings
4.5 Recommendations for Future Research

Chapter 5: Conclusion and Summary
5.1 Summary of Findings
5.2 Conclusion
5.3 Contributions to the Field
5.4 Practical Implications
5.5 Limitations and Recommendations for Future Research

Brief Overview:

The thesis on Data Analytics for Social Network Analysis aims to explore the application of data mining techniques in analyzing and understanding social networks. The study focuses on leveraging data analytics to extract valuable insights from large datasets collected from social networks.

Chapter one provides an introduction to the study, outlining the research problem, objectives, significance, limitations, and scope of the study. Chapter two reviews relevant literature on data analytics, social network analysis, data mining techniques, and their applications in social network analysis.

Chapter three discusses the research methodology, including research design, data collection methods, analysis techniques, sampling procedures, and ethical considerations. Chapter four presents the findings of the data analysis, interpretation of results, comparison with existing literature, implications, and recommendations for future research.

Finally, chapter five concludes the thesis with a summary of findings, conclusions, contributions to the field, practical implications, limitations, and recommendations for future research. The study aims to contribute to the field of social network analysis by demonstrating the effectiveness of data analytics in extracting meaningful insights from social network data.

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