Discovering Organizational Hierarchy through a Corporate Ranking Algorithm: The Enron Case

<div>Clusters and features by two main principal components according to <i>K</i>-means (a) and the PCA CorpRank score (b) for Enron. The distance between each feature and the origin is proportional to the quality of its representation on the factor map. Feature definition is in Algorithm 1. (a) Clusters by <i>K</i>-means. (b) Clusters by PCA CorpRank score.</div>

Complexity

fig2

Figure 2

Figure 2: Discovering Organizational Hierarchy through a Corporate Ranking Algorithm: The Enron Case 