Layered Ego Networks in Email Communication: From Enron to the Jmail Archive

2026-06-01

AI Summary

This study investigates the applicability of Dunbar’s classic layered model of social structure to email communication, with a focus on identifying social relationship tiers in high-frequency, single-topic interaction contexts. Recognizing that standard layering approaches fail in such settings, the authors propose a frequency-normalization strategy grounded in the support of cohesive subgroups. By integrating clustering, threshold-based layering, reciprocity tests, and frequency analysis, they successfully reproduce Dunbar-like structures in the Enron email dataset. Furthermore, applying their normalization method to the Jmail high-frequency dataset reveals clear, interpretable layers of genuine bidirectional relationships. These findings demonstrate that meaningful social stratification remains recoverable and analyzable even under conditions of extreme communication intensity.

Abstract

Email archives offer a rare view of social relationships through repeated communication, but it remains unclear how well classical ego network layering applies to digital interaction data. This paper compares two public email archives with sharply contrasting structures: Enron, a workplace corpus involving around 150 users, and Jmail, a single-ego archive centered on an exceptionally active focal actor whose communication volume is more than twenty times higher than the average Enron user. We ask, in each case, whether Dunbar-like layered organization is recoverable from email communication frequency and how it should be interpreted. For Jmail, we show that extreme communication intensity causes standard layering methods (whether clustering-based or threshold-based) to break down. Jmail is not a broad communication environment with many occasional contacts, but a selective pool of high-interest alters operating on a much higher frequency scale than ordinary email. Once the Dunbar frequency ladder is anchored to the empirical support-clique boundary, a clearer layered structure emerges. Reciprocity analysis confirms that the recovered layers reflect genuine bidirectional relationships rather than artifacts of the focal actor's outgoing activity. Enron serves as a workplace benchmark that grounds the comparison: its ego networks partially reproduce Dunbar-like organization, with stable inner circles and an outermost recovered layer corresponding to Dunbar's affinity group ($\sim50$), confirming that layered structure is recoverable from ordinary organizational email. Overall, the findings show that Dunbar-like organization can be meaningfully studied in email archives, but that selective high-frequency archives require frequency normalization before the layered structure becomes interpretable.

Problem

• ego networks
• email archives
• Dunbar layers
• communication frequency
• social structure

Innovation

• ego networks
• Dunbar layers
• email archives
• frequency normalization
• reciprocity analysis