BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Historical Network Research - ECPv4.9.2//NONSGML v1.0//EN CALSCALE:GREGORIAN METHOD:PUBLISH X-WR-CALNAME:Historical Network Research X-ORIGINAL-URL: X-WR-CALDESC:Events for Historical Network Research BEGIN:VEVENT DTSTART;VALUE=DATE:20180709 DTEND;VALUE=DATE:20180728 DTSTAMP:20190521T210008 CREATED:20180331T212632Z LAST-MODIFIED:20180331T212857Z SUMMARY:Introduction and Advanced SNA courses at Essex Summer School (July 2018) DESCRIPTION: Dear All\, \nThis summer the Essex Summer School (University of Essex\, UK) will again offer an introductory as well as an advanced course on Social Network Analysis. \n1) Introduction to Social Network Analysis (2 weeks\, 9-20 July 2018) \nContent. The course focuses on the description and visualization of social network data using UCINET. We will concentrate on uncovering structural properties of the network (e.g. density\, homophily\, and clustering)\, as well as on how to identify important persons in a network (e.g. degree centrality\, structural holes\, …). We will also pay attention to the detection of subgroups and deal with basic hypothesis testing for social network analysis. Throughout the course some classic theories that focus on network processes (e.g. related to homophily\, centrality measures\, structural holes\, Granovetter’s strength of weak ties and small worlds) will be discussed. \nMore information at: \n2) Advanced Social Network Analysis: Cross-sectional and longitudinal SNA (1 week\, 23-27 July 2018) \nContent. This module covers advanced statistical methods for analyzing social network data\, focusing on testing hypotheses about network structure (e.g. reciprocity\, transitivity\, and closure)\, and the formation of ties based on attributes (e.g. homophily). The first three days provide an in depth discussion of exponential random graph models (also known as ERGM or p* models). We then introduce longitudinal models such as RSiena models (SAOMs) and relational event models. \nMore information at: \nPlease feel free to forward to anyone that you think might be interested. \nBest wishes\, \nFilip \n_________ \n\n\n Related\n URL: END:VEVENT END:VCALENDAR