Finding Astronomical Communities Through Co-readership Analysis

TL;DR

This paper explores how co-readership data from the NASA/Smithsonian Astrophysics Data System can reveal communities of astronomers by analyzing shared paper reading patterns, using various mathematical representations.

Contribution

It introduces a novel approach to identify astronomical communities through co-readership analysis using spectral and principal component methods.

Findings

Co-readership reveals structured communities within astronomers.

Spectral density and PCA effectively represent community structures.

Initial classification of astronomical communities based on co-readership patterns.

Abstract

Whenever a large group of people are engaged in an activity, communities will form. The nature of these communities depends on the relationship considered. In the group of people who regularly use scholarly literature, a relationship like ``person i and person j have cited the same paper'' might reveal communities of people working in a particular field. On this poster, we will investigate the relationship ``person i and person j have read the same paper''. Using the data logs of the NASA/Smithsonian Astrophysics Data System (ADS), we first determine the population that will participate by requiring that a user queries the ADS at a certain rate. Next, we apply the relationship to this population. The result of this will be an abstract ``relationship space'', which we will describe in terms of various ``representations''. Examples of such ``representations'' are the projection of co-read vectors onto Principal Components and the spectral density of the co-read network. We will show that the co-read relationship results in structure, we will describe this structure and we will provide a first attempt in the classification of this structure in terms of astronomical communities. The ADS is funded by NASA Grant NNG06GG68G.