fauci-email: a json digest of Anthony Fauci's released emails

Abstract

A collection of over 3000 pages of emails sent by Anthony Fauci and his staff were released in an effort to understand the United States government response to the COVID-19 pandemic. We describe how this email data was translated into a resource consisting of json files that make many future studies easy. Findings from our processed data include (i) successful organizational partitions using the simple mincut techniques in Zachary's karate club methodology, (ii) a natural example where the normalized cut and minimum conductance set are extremely different, and (iii) organizational groups identified by optimal modularity clusters that illustrate a working hierarchy. These example uses suggest the data will be useful for future research and pedagogical uses in terms of human and system behavioral interactions. We explain a number of ways to turn email information into a network, a hypergraph, a temporal sequence, and a tensor for subsequent analysis as well as a few examples of such analysis.

Weighted Enumeration of Nonbacktracking Walks on Weighted Graphs

“…We further examine the effect of weighting edges on the rankings produced by both centrality measures. To this end, we consider the Katz centrality formula (5.2) as applied to one static network and one temporal network, both derived from the same data set (Fauci's email release [6]) 2 . The original dataset is a collection of over 3000 pages of emails involving Anthony Fauci and his staff during the COVID-19 pandemic.…”

“…Data includes sender and receivers (including CC'd) of emails, as well as time stamps of when the emails were sent. Both networks used in the following were presented in [6].…”

“…Analysis on Static Networks. In this section, we analyze a static network produced by [6] which is both undirected and weighted. We have an edge (i, j) if there exists an email which involves both nodes i and j as any combination of sender and recipient (including CC'd recipients).…”