This project aims to perform Social Network Analysis (SNA) on the Slashdot dataset to understand the relationships and interactions between users within the Slashdot community. The dataset consists of friend and foe relationships between the users of Slashdot, gathered in February 2009.
Information about the dataset can be found in the Dataset Information.md file, in the parent folder of this project. The data file is named soc-Slashdot0902.txt, and is available in the parent directory.
Data Preparation: In this stage, we will preprocess the dataset, clean it, and transform it into a suitable format for analysis. This may involve removing duplicates, handling missing data, and formatting the dataset into a network graph.
Exploratory Data Analysis (EDA): EDA will be performed to obtain a better understanding of the dataset, including node and edge distributions, degree distributions, and other relevant statistics.
Community Detection: We will identify and analyze communities within the Slashdot network. This may involve using clustering algorithms or modularity-based approaches to group users with similar interests or relationships.
Centrality Measures: We will compute and analyze various centrality measures such as degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality to identify influential users within the network.
Visualization: We will create visualizations to better understand the network structure, including node-link diagrams, adjacency matrices, and heatmaps.
Understanding the community structure and dynamics
Visual representations of the network structure, communities and other findings
Identification of influential users within the Slashdot community
Prediction of potential new relationships between users