471 citations · 1.7k across the 25 of their papers we have counts for
8 papers · 1 filter
An Open-Source Cultural Consensus Approach to Name-Based Gender Classification
Ian Van Buskirk, Aaron Clauset, Daniel B. Larremore
Name-based gender classification has enabled hundreds of otherwise infeasible scientific studies of gender. Yet, the lack of standardization, proliferation of ad hoc methods, relia…
A guide to choosing and implementing reference models for social network analysis
Elizabeth A. Hobson, Matthew J. Silk, Nina H. Fefferman +4
Analyzing social networks is challenging. Key features of relational data require the use of non-standard statistical methods such as developing system-specific null, or reference,…
Explaining Gender Differences in Academics' Career Trajectories
Aniko Hannak, Kenneth Joseph, Andrei Cimpian +1
Academic fields exhibit substantial levels of gender segregation. To date, most attempts to explain this persistent global phenomenon have relied on limited cross-sections of data…
Emergence of Hierarchy in Networked Endorsement Dynamics
Mari Kawakatsu, Philip S. Chodrow, Nicole Eikmeier +1
Many social and biological systems are characterized by enduring hierarchies, including those organized around prestige in academia, dominance in animal groups, and desirability in…
Community detection, link prediction, and layer interdependence in multilayer networks
Caterina De Bacco, Eleanor A. Power, Daniel B. Larremore +1
Complex systems are often characterized by distinct types of interactions between the same entities. These can be described as a multilayer network where each layer represents one…
The ground truth about metadata and community detection in networks
Leto Peel, Daniel B. Larremore, Aaron Clauset
Across many scientific domains, there is a common need to automatically extract a simplified view or coarse-graining of how a complex system's components interact. This general tas…
Gender, Productivity, and Prestige in Computer Science Faculty Hiring Networks
Samuel F. Way, Daniel B. Larremore, Aaron Clauset
Women are dramatically underrepresented in computer science at all levels in academia and account for just 15% of tenure-track faculty. Understanding the causes of this gender imba…
Efficiently inferring community structure in bipartite networks
Daniel B. Larremore, Aaron Clauset, Abigail Z. Jacobs
Bipartite networks are a common type of network data in which there are two types of vertices, and only vertices of different types can be connected. While bipartite networks exhib…