Two new IMBS technical reports by Lab PI Butts are now available on the IMBS web site. The first, “A Note on Generalized Edges” (MBS 10-03) introduces basic terminology and formalisms for representing complex multi-party relationships, facilitating the treatment of phenomena such as joint task performance, mental models, and actor/bystander interactions that are difficult to model using traditional network analytic approaches. The second paper, “Bayesian Meta-Analysis of Social Network Data via Conditional Uniform Graph Quantiles” (MBS 10-04) provides a family of techniques for leveraging a well-known tool for analyzing individual networks — conditional uniform graph quantiles — to draw inferences regarding populations of networks from sampled data. These methods are especially applicable to meta-analytic applications, in which one seeks to pool information from multiple case studies. Both of these papers showcase our current research on methods for the analysis of network data, with an emphasis on tools and ideas that can be applied in practical settings.
Calit2 article highlights findings from a recent paper by Lab members Butts and Cross. Published in the Journal of Social Structure, this paper shows how blog networks during the 2004 election season evolved in response to both events on the campaign trail and to the cycles of everyday life. To learn more, see the original paper and theCalit2 feature.
Six R packages which contain the 2000 US Census spatial data at four different geographies (Block, Block Group, Tract, and Census Designated Places), includes selected demographics, and a series of functions dedicated to managing and manipulating the data. These data sets and helper functions can be found on this website on CRAN.
We are pleased to announce the release of scrapeR, a new software package for the R computing platform created by NCASD lab member Ryan Acton. The scrapeR package contains tools that assist with the extraction of information embedded in web pages. With this new tool, users can automate the retrieval of information from web-based sources and diagnose potential problems. Researchers familiar with R will likely find this tool helpful, as it allows for the collection of data entirely within the R environment. This, combined with the powerful data analytic capabilities available to R users, makes this an attractive piece of software. The scrapeR package is available for download here.