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:20180702 DTEND;VALUE=DATE:20180714 DTSTAMP:20190624T233552 CREATED:20180316T161932Z LAST-MODIFIED:20180317T120331Z SUMMARY:Summer School in Social Network Analysis\, Manchester DESCRIPTION:***** To join INSNA\, visit ***** \nDear colleagues \nThe Mitchell Centre for Social Network Analysis at the University of Manchester is organising two modules on SNA for the annual summer school of Methods@Manchester. \nInfo and registrations are available at \n \nThis year we offer: \n\nIntroduction to SNA using Ucinet and Netdraw\n\n2-6 July \nThis is an introductory course\, covering the concepts\, methods and data analysis techniques of social network analysis. The course is based on the book “Analyzing Social Networks” by Borgatti et al. (Sage) and all participants will be issued with a copy of the book. The course begins with a general introduction to the distinct goals and perspectives of social network analysis\, followed by a practical discussion of network data\, covering issues of collection\, validity\, visualization\, and mathematical/computer representation. We then take up the methods of detection and description of structural properties\, such as centrality\, cohesion\, subgroups and positional analysis techniques. This is a hands on course largely based around the use of UCINET software\, and will give participants experience of analyzing real social network data using the techniques covered in the workshop. No prior knowledge of social network analysis is assumed for this course. \n\nStatistical analysis of social networks\n\n9-13 July \nThis is an introduction to statistical analysis of networks. While no strict prerequisites are assumed\, you might find it helpful to have some basic knowledge of social network analysis beforehand. To benefit fully from the course requires a basic knowledge of standard statistical methods\, such regression analysis. The course aims to give a basic understanding of and working handle on drawing inference for structure and attributes\, both cross-sectionally as well as longitudinally. A fundamental notion of the course will be how the structure of observed graphs relate to various forms of random graphs. This will be developed in the context of non-parametric approaches and elaborated to analysis of networks using exponential random graph models (ERGM) and stochastic actor-oriented models. The main focus will be on explaining structure but an outlook to explaining individual-level outcomes will be provided. The participant will be provided with several hands-on exercises\, applying the approaches to a suite of real world data sets. We will use the stand-alone graphical user interface package MPNet and R. In R we will learn how to use the packages ‘sna’\, ‘statnet’\, and ‘RSiena’. No familiarity with R is assumed but preparatory exercises will be provided ahead of the course. best \nElisa Bellotti \nDepartment of Sociology \nand \nMitchell Centre for Social Network Analysis \n \n \nUniversity of Manchester \nArthur Lewis Building \nRoom 3.029 \nBridgeford Street \nManchester M13 9PL \n+44(0)1612752512 \n_____________________________________________________________________ SOCNET is a service of INSNA\, the professional association for social network researchers ( To unsubscribe\, send an email message to containing the line UNSUBSCRIBE SOCNET in the body of the message. \n\n\n Related\n URL: END:VEVENT END:VCALENDAR