K
Katherine Faust
Researcher at University of California, Irvine
Publications - 58
Citations - 34902
Katherine Faust is an academic researcher from University of California, Irvine. The author has contributed to research in topics: Social network & Social network analysis (criminology). The author has an hindex of 29, co-authored 58 publications receiving 34066 citations. Previous affiliations of Katherine Faust include University of South Carolina & University of California.
Papers
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Book ChapterDOI
Social Network Analysis: Centrality and Prestige
TL;DR: This chapter presents and discusses a variety of measures designed to highlight the differences between important and non-important actors, and discusses the most noteworthy and substantively interesting definitions of importance or prominence.
Journal ArticleDOI
Correlation and association models for studying measurements on ordinal relations
TL;DR: Correlation and association models are especially useful for studying discrete ordinal variables, which arise quite frequently in the social and behavioral sciences as discussed by the authors, and have been shown to be useful for measuring the order and spacing of categories of ordinal relational variables.
Indicators and Peer Groups for Transit Performance Analysis
TL;DR: In this paper, the second year (1979-80) of the Section 15 statistics are used, first to test the validity of a small set of performance indicators for fixed-route bus operations, and second to define relatively homogeneous groups of operators (peer groups) that can be compared.
Journal ArticleDOI
Discussion on the paper by Handcock, Raftery and Tantrum
Tom A. B. Snijders,Tony Robinson,Anthony C. Atkinson,Marco Riani,Isobel Claire Gormley,Thomas Brendan Murphy,Trevor Sweeting,David S. Leslie,Nicholas T. Longford,John T. Kent,Tony Lawrance,Edoardo M. Airoldi,Julian Besag,David M. Blei,Stephen E. Fienberg,Ronald L. Breiger,Carter T. Butts,Patrick Doreian,Vladimir Batagelj,Anuška Ferligoj,David Draper,Marijtje A. J. van Duijn,Katherine Faust,Miruna Petrescu-Prahova,Jonathan J. Forster,Andrew Gelman,Steven M. Goodreau,Priscilla E. Greenwood,Katharina Gruenberg,Brian Francis,Christian Hennig,Peter D. Hoff,David R. Hunter,Dirk Husmeier,Chris A. Glasbey,David Krackhardt,Jouni Kuha,Anders Skrondal,Andrew B. Lawson,Tim Futing Liao,Bruno Mendes,Gesine Reinert,Sylvia Richardson,Alex Lewin,D. M. Titterington,Stanley Wasserman,Adriano Velasque Werhli,Peter Ghazal +47 more
TL;DR: Leslie et al. as mentioned in this paper showed that the Markov chain Monte Carlo sampling scheme that was used results in extremely slow mixing, requiring 2 million iterations with only every 1000th iteration being used.