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Analyzing Collaboration Networks Using Simplicial Complexes: A Case Study
| Citations: | 2 - 2 self |
BibTeX
@MISC{Moore_analyzingcollaboration,
author = {T. J. Moore and R. J. Drost and P. Basu and R. Ramanathan and A. Swami},
title = {Analyzing Collaboration Networks Using Simplicial Complexes: A Case Study},
year = {}
}
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Abstract
Abstract—Collaboration social networks are traditionally modeled using graphs that capture pairwise relationships but have ambiguity between group collaborations and multiple pairwise collaborations. We present a new approach to analyzing collaboration networks using simplicial complexes to represent the co-authorship collaborations. We formally define several key novel metrics: 1) higher dimensional analogs of vertex degree (e.g., simplex and facet degrees), 2) homology, and 3) minimal non-faces; and discuss their interpretation as it relates to coauthorship. We use these metrics in a study of an Army Research Lab dataset that includes the publications of the Communications & Networks Collaborative Technology Alliance. In particular, our study reveals many properties of large networks mirrored by this single-program publication dataset: the distinction of certain simplex degrees from vertex degrees, a power law characteristic in facet degrees, and some properties of topological “holes ” and minimal non-faces. I.
Keyphrases
collaboration network using simplicial complex case study minimal non-faces facet degree vertex degree large network army research lab new approach capture pairwise relationship collaboration network several key novel metric certain simplex degree power law characteristic group collaboration topological hole simplicial complex co-authorship collaboration multiple pairwise collaboration abstract collaboration social network dimensional analog study reveals many property communication network collaborative technology alliance single-program publication dataset
