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Analysing key-influential figures in Donald-Trump's Network who helped him rise to fame.

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TrumpWorld_DA

Analyzing key-influential figures in Donald-Trump's Network who helped him rise to fame.

The Dataset and Task:

Trump world dataset is a dataset built from multiple resources on the Trump family, his cabinet picks and top advisers. The Task of this project is to identify pivotal figures that helped Donald Trump rise to fame.

The Solution Process:
  • Data Preparation: use python and pandas library to organize data and remove unimportant entities (such as organizations).
  • Data Modeling: constructing a graph representing the different nodes in the network and preform graph descriptive statistics.
  • Centralities Study: deep dive into centralities to identify key nodes in the graph and hence detect influential people in the Trump network.
  • Exploratory Data Analysis (EDA): using network science tools and Data Visualization techniques to extract Basic attributes and the network summary,
  • Statistical Study: to find out if the network is randomly structured and the closest random graph to my social network.
  • Centralities Study: to identify key people in my social network and their importance.
  • Data Visualization: draw the graphs in order to deepen our understanding of the key-influential people effect.
The Findings:
  • Extracted multiple influential people from Trump network.
  • Gephi Folder contains multiple interactive visualization of the network under study.
  • identify in which way those influential people affected Trump rise to fame.

Skills developed: pandas | networkx | Gephi | numpy | networkx | Centralities Analysis | Data Processing | EDA | Statistical Analysis | python | Data Visualization | Network Science.

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