Calculate relevant network measures

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Reference no: EM133694844

Question: Please provide detailed instructions for collecting data from LinkedIn, including user profiles and connections, while ensuring that all necessary credentials, such as an API key, are in place. The objective is to gather sufficient data to create a social network with 100-500 nodes.

Instructions:

Apply for LinkedIn API access and obtain the required credentials (API key, secret, etc.).

Utilize a Python library like python-linkedin or linkedin-api to interact with the LinkedIn API.

Collect user profiles and connections data within the API's rate limits and permissions.

Organize and structure the collected data to prepare it for network analysis.

Choose a network analysis library such as NetworkX, SNAP, Gephi, NodeXL, or graph-tool to visualize the data as a graph.

Ensure that the data is in an appropriate format for your chosen graph analysis software (e.g., adjacency matrix, adjacency list, edge list).

Utilize your chosen graph analysis software to create a visualization of the LinkedIn social network.

Calculate relevant network measures, such as degree distribution, clustering coefficient, PageRank, diameter, closeness, and betweenness, using functions available in your chosen graph analysis software.

Reference no: EM133694844

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