Network Analysis with the Enron Email Corpus

TL;DR

This paper explores the use of the Enron email corpus to analyze social network relationships through six centrality measures, providing educational insights and research opportunities for undergraduate students.

Contribution

It demonstrates how the Enron corpus can be used to teach and research network analysis, focusing on centrality measures and their implications.

Findings

Analysis of centrality measures in Enron email network

Educational value for undergraduate research

Potential for broader social network and NLP studies

Abstract

We use the Enron email corpus to study relationships in a network by applying six different measures of centrality. Our results came out of an in-semester undergraduate research seminar. The Enron corpus is well suited to statistical analyses at all levels of undergraduate education. Through this note's focus on centrality, students can explore the dependence of statistical models on initial assumptions and the interplay between centrality measures and hierarchical ranking, and they can use completed studies as springboards for future research. The Enron corpus also presents opportunities for research into many other areas of analysis, including social networks, clustering, and natural language processing.