Social network analysis and community detection
Table Of Contents
<p>1. Introduction<br> 1.1 Importance of social network analysis and community detection<br> 1.2 Research objectives<br>2. Literature review<br> 2.1 Fundamentals of social network analysis<br> 2.2 Community detection algorithms and methodologies<br> 2.3 Applications of community detection in real-world scenarios<br>3. Data collection and network representation<br> 3.1 Selection of social network datasets<br> 3.2 Data preprocessing and network construction<br> 3.3 Visualization and analysis of network properties<br>4. Community detection algorithms<br> 4.1 Overview of community detection methods<br> 4.2 Development of novel algorithms for large-scale networks<br> 4.3 Comparative evaluation of community detection techniques<br>5. Case studies and experiments<br> 5.1 Application of community detection to real-world social networks<br> 5.2 Analysis of community structures and dynamics<br></p>
Thesis Abstract
<p> Social network analysis plays a crucial role in understanding the structure and dynamics of online communities, enabling insights into information diffusion, influence propagation, and community detection. This project aims to conduct a comprehensive study of social network analysis techniques and develop algorithms for community detection in large-scale networks. The study will involve data collection, network representation, algorithm design, and evaluation using real-world social network datasets. The outcomes of this project will contribute to advancing our understanding of online social interactions and supporting applications such as targeted marketing and content recommendation. <br></p>Thesis Overview
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