Welcome to the XXXIX Sunbelt Social Networks Conference of the International Network for Social Network Analysis (INSNA). Here are some conference-related information... There are more on the Conference Website (you can download some helpful documents directly from the home page, under ’’Shared Files’’). WiFi: Network: Visiteurs UQAM User name: asunbelt2019 Password: DQ32fK23 OR EDUROAM is also available everywhere in all UQAM Buildings. There is also a Public WIFI Network in Downtown Montréal: MTL-WIFI (see here for more details). RESTAURANTS There is no lack of good restaurants and bars near the Conference venue and in Montréal globally. Download the pdf file for a few suggestions (under ’’Shared Files’’ on the website).
During our workshop we will present the network approach to bibliographic data and different methods used for their analysis, covering the questions of getting and preparing networks. Among others, we will present a measure of collaborativeness of authors with respect to a given bibliography and show how to compute the network of citations betwenn authors and identify citation communities. The participants will be able to collect bibliographic data, construct the corresponding networks and apply the discussed techniques of network analysis to them. We will use a program Pajek, supported by some special programs in Python and R. Workshop materials will be available at GitHub: https://github.com/bavla/BibNets.
This workshop will provide a hands-on introduction to new software, statnetWeb, that provides a simple point-and-click interface for the statistical analysis of network data, including ERGMs. It is intended both for newbies to statistical network modeling, and for instructors seeking a robust software application for teaching introductory network analysis courses. Topics covered include: uploading network data, using plots and descriptive statistics to learn about the network, fitting exponential-family random graph models (ERGMs), model diagnostics, goodness of fit, and simulations. statnetWeb allows users to focus on concepts, rather than code. It runs in a web browser window, providing access to the functionality of the statnet suite of R packages without the need to learn R programming or, in some cases, download or install R and statnet. The app can be used as a stand-alone software application, or as a bridge to learn the traditional command-line statnet software in R.
