Complete Analysis of Amazon' Co-Purchasing Network
In this project, we dive into the Amazon product co-purchasing network to explore the connections between products and identify key patterns and communities within the network. By leveraging social network analysis techniques, we aim to gain a deeper understanding of the product network's structure, identify influential products, and uncover potential clusters or communities of related items.
- Run "Amazon_Co-purchased Product Analysis.ipynb"
- Make Sure You Have The CSV Files I have Provided
We utilize a large-scale dataset obtained from Amazon, which contains information about customer purchases and the co-purchasing relationships between products. The dataset includes attributes such as product IDs, customer IDs, purchase timestamps, and additional metadata about the products.
Raw Data can be obtained from:-- Stanford's Network Datasets
- analysis involves several key steps:
- Data preprocessing: We perform data cleaning and transformation to ensure the dataset is in a suitable format for network analysis.
- Network construction: We construct a co-purchasing network by representing products as nodes and connecting them based on their co-purchasing relationships.
- Network analysis: We apply various social network analysis techniques to explore the structural properties of the co-purchasing network. This includes measuring centrality, identifying communities or clusters, and examining network connectivity.
- Visualization: We visualize the co-purchasing network and its key properties to provide a clear representation of the relationships between products and any identified patterns or communities.