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CORRECTION: The earlier announcement identified this as an INSNA Sunbelt workshop. That was a typo. The workshop is sponsored by MSU Social Science Data Analytics. INSNA/Sunbelt
participants are, of course, still welcome to participate.
Virtual Social Science Data Analytics Workshop
TITLE: Introduction to bipartite projection networks and backbones
PRESENTERS: Zachary Neal, Rachel Domagalski, Bruce Sagan (Michigan State University)
DATE/TIME: 13 July 2020, 10am-11am EDT
COST: None. Participation in this workshop is free and open to everyone.
This workshop will be hands-on and interactive. Participants who want to follow along should download backbone.zip from
, expand the zip file, and follow the instructions in the readme.rtf before the workshop begins.
DESCRIPTION: Social networks can be difficult to collect, but they can sometimes be inferred from easy-to-collect bipartite data. For example, we might infer that
pairs of legislators are collaborators if they have sponsored many bills together (e.g. a bill co-sponsorship network), or that pairs of people are friends if they have attended many events together (e.g. an event co-attendance network). These are examples
of bipartite projection networks, which can offer a practical way to measure social networks, but which also require special techniques for analysis. In particular, we must decide how many bills two legislators must sponsor together, or how many events two
people must attend together before we can count them as collaborators or friends. This workshop will provide an introduction to bipartite projection networks and their analysis using the backbone package for R. Basic familiarity with networks (e.g. what they
are) and with R (e.g. how to load data and packages) will be helpful, but otherwise this workshop is intended for both beginners and advanced users.
Zachary Neal, PhD
Associate Professor, Michigan State University
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