FAKE NEWS DETECTION USING GRAPH-BASED CLUSTERING TECHNIQUES

1. Introduction 1.1 Background of Fake News 1.2 Importance of Detection 1.3 Research Objectives 1.4 Structure of the Paper 2. Literature Review 2.1 Fake News Characteristics 2.2 Traditional Detection Methods 2.3 Graph-Based Techniques Overview 3. Methodology 3.1 Research Design and Approach 3.2 Data Collection and Preprocessing 3.3 Graph-Based Clustering Techniques 4. Graph Theory Basics 4.1 Fundamental Concepts 4.2 Graph Representation of Data 4.3 Node and Edge Significance 5. Clustering Techniques 5.1 Clustering Algorithm Selection 5.2 Graph Construction Methods 5.3 Evaluation Metrics for Clusters 6. System Implementation 6.1 Software and Tools Used 6.2 Implementation Process Steps 6.3 Challenges and Solutions 7. Results and Analysis 7.1 Experiment Setup and Parameters 7.2 Comparison with Other Methods 7.3 Impact on Detection Accuracy 8. Conclusion and Future Work 8.1 Summary of Findings 8.2 Contributions to the Field 8.3 Recommendations for Future Research