72 citations · 293 across the 12 of their papers we have counts for
12 papers
When can networks be inferred from observed groups?
Zachary P. Neal
Collecting network data directly from network members can be challenging. One alternative involves inferring a network from observed groups, for example, inferring a network of sci…
Stochastic Degree Sequence Model with Edge Constraints (SDSM-EC) for Backbone Extraction
Zachary P. Neal, Jennifer Watling Neal
It is common to use the projection of a bipartite network to measure a unipartite network of interest. For example, scientific collaboration networks are often measured using a co-…
A stopping rule for randomly sampling bipartite networks with fixed degree sequences
Zachary P. Neal
Statistical analysis of bipartite networks frequently requires randomly sampling from the set of all bipartite networks with the same degree sequence as an observed network. Trade…
The duality of networks and groups: Models to generate two-mode networks from one-mode networks
Zachary P. Neal
Focus theory describes how shared memberships, social statuses, beliefs, and places can facilitate the formation of social ties, while two-mode projections provide a method for tra…
backbone: An R package to extract network backbones
Zachary P. Neal
Networks are useful for representing phenomena in a broad range of domains. Although their ability to represent complexity can be a virtue, it is sometimes useful to focus on a sim…
fastball: A fast algorithm to sample bipartite graphs with fixed degree sequences
Karl Godard, Zachary P. Neal
Many applications require randomly sampling bipartite graphs with fixed degrees, or randomly sampling incidence matrices with fixed row and column sums. Although several sampling a…
Comparing Alternatives to the Fixed Degree Sequence Model for Extracting the Backbone of Bipartite Projections
Zachary P. Neal, Rachel Domagalski, Bruce Sagan
Projections of bipartite or two-mode networks capture co-occurrences, and are used in diverse fields (e.g., ecology, economics, bibliometrics, politics) to represent unipartite net…
Identifying hidden coalitions in the US House of Representatives by optimally partitioning signed networks based on generalized balance
Samin Aref, Zachary P. Neal
In network science, identifying optimal partitions of a signed network into internally cohesive and mutually divisive clusters based on generalized balance theory is computationall…
backbone: An R Package for extracting the backbone of bipartite projections
Rachel Domagalski, Zachary Neal, Bruce Sagan
Bipartite projections are used in a wide range of network contexts including politics (bill co-sponsorship), genetics (gene co-expression), economics (executive board co-membership…
False positives using social cognitive mapping to identify childrens' peer groups
Zachary Neal, Jennifer Watling Neal, Rachel Domagalski
Children and adolescents interact in peer groups, which are known to influence a range of psychological and behavioral outcomes. In developmental psychology and related disciplines…
Detecting coalitions by optimally partitioning signed networks of political collaboration
Samin Aref, Zachary Neal
We propose new mathematical programming models for optimal partitioning of a signed graph into cohesive groups. To demonstrate the approach's utility, we apply it to identify coali…
Navigating the massive world of reddit: Using backbone networks to map user interests in social media
Randal S. Olson, Zachary P. Neal
In the massive online worlds of social media, users frequently rely on organizing themselves around specific topics of interest to find and engage with like-minded people. However,…