This is an academic project that involves the analysis of a dataset containing patents related to electric batteries in the automotive industry. The analysis is conducted by building a network using Python and consists of the following steps:
Preliminary exploration and examination of the dataset.
The dataset is used to construct a network using Python. Cluster analysis is performed to identify 5 clusters within the network. The Louvain algorithm is applied to determine the ultimate parent variable for each cluster. Two output files, namely cluster_map.txt and network_edges.txt, are generated to facilitate data visualization using Vosviewer software.
Further cluster analysis is conducted, this time focusing on technology classes within the dataset. This project aims to gain insights into the patent landscape of electric vehicle batteries and their related technologies through network analysis and clustering techniques.