***** To join INSNA, visit http://www.insna.org ***** Dear all, The University of Exeter Centre for Social Networks is offering a 5-day workshop on “The analysis of social networks: From description to statistical modelling.” The workshop will take place from June 22nd to June 26th 2020 and will be led by Professor Alessandro Lomi and Dr Viviana Amati. For further information and for registration, please read below or visit our Webpage: https://urldefense.proofpoint.com/v2/url?u=https-3A__business-2Dschool.exeter.ac.uk_research_centres_ecsn_events_introductory-2Dworkshop_&d=DwIF-g&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=FYJf-6EYeYqoN716BHO1Uz-zcERfnr5z6446By4f7qk&s=W2dJDWBp0uK_Q3GjftM6-o6rP9n0LXfB7s3eZoO9CjU&e= <https://urldefense.proofpoint.com/v2/url?u=https-3A__eur03.safelinks.protection.outlook.com_-3Furl-3Dhttps-253A-252F-252Furldefense.proofpoint.com-252Fv2-252Furl-253Fu-253Dhttps-2D3A-5F-5Fbusiness-2D2Dschool.exeter.ac.uk-5Fresearch-5Fcentres-5Fecsn-5Fevents-5Fintroductory-2D2Dworkshop-5F-2526d-253DDwMF-2Dg-2526c-253DsJ6xIWYx-2DzLMB3EPkvcnVg-2526r-253DyQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w-2526m-253DN4EfvJo8Zls9njqkAOzRb-5FzsM-5F1wGPi2Zjgm5sSHzLw-2526s-253DASb-5F54D6rAGVpnToKMPPD-2DXdABbsj7ZxK-2Dpl0q4DXDg-2526e-253D-26data-3D02-257C01-257CA.Parker3-2540exeter.ac.uk-257Cb2e8d64ea4b849c9d4cb08d77d5a7c1a-257C912a5d77fb984eeeaf321334d8f04a53-257C0-257C0-257C637115699889677264-26sdata-3DGdlxMv0epmv7RmMx-252B1dkwn8TFnjBhz-252FshM5B2WKF4RM-253D-26reserved-3D0&d=DwIF-g&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=FYJf-6EYeYqoN716BHO1Uz-zcERfnr5z6446By4f7qk&s=oqPxw1pwiq20JuoWobHkbM6-kNe30kYTH4aM6eLC2dY&e= > Contents and objectives: Data typically collected in the social sciences rely on the familiar case-by-variable research design, where "cases" (rows) represent various kinds of social actors, and "variables" (columns) contain measurements on a set of attributes of the actors or their context. Quantitative research based on this design typically emphasizes relations among the "variables." Social network research, by contrast, focuses on relations among the "cases." This change of perspective requires the development of specialized models and methods to represent, describe and analyse relational data. The course starts by introducing the basic theoretical and conceptual background of social network research, the fundamental ideas underlying the network approach, and discusses its many domains of empirical application. The course then proceeds to examine the basic analytical concepts needed to describe and understand the structure of social networks across various levels of analysis. Participants will learn how to visualize social network data to discover their main structural features, and how to implement different types of network research designs and approaches to data collection. The course also introduces contemporary statistical models for social networks, so that participants may learn how to test hypotheses using network data. Permutation tests (QAP), Exponential Random Graphs models (ERGMs) and Stochastic Actor-oriented Models (SAOMs) will be introduced as examples of statistical models for studying network structure and connective behavior. The course will include practical examples and hands-on computer laboratories based on the analysis of real-life relational data. In the laboratories, the emphasis will be on the analysis of social networks in structured social and economic settings such as, for example, business companies, and other formal organizations like hospitals, universities and other educational institutions. Students will also be given the opportunity to work with their own data and consult privately with the instructors about their own research work and problems. Software resources: The software packages that will be introduced during the workshop include Statnet, Visone, PNet and RSIENA. The software resources used in the course are all publicly and freely available. Depending on the interests of the participants, specialized software resources developed for the R environment may also be illustrated. Prerequisites: Participants taking this course are expected to be familiar with the basic concepts of descriptive statistics, and have an active interest in statistical inference. The basic elements of the R programming language needed to specify, estimate, and interpret network models will be introduced in the early stages of the seminar. Andrew Parker Professor of Business Director of Exeter Centre for Social Networks (ECSN) University of Exeter Business School email: [log in to unmask] Streatham Court, University of Exeter, Rennes Drive, Exeter, EX4 4PU, UK [bs_2019] This email and any attachment may contain information that is confidential, privileged, or subject to copyright, and which may be exempt from disclosure under applicable legislation. It is intended for the addressee only. If you received this message in error, please let me know and delete the email and any attachments immediately. The University will not accept responsibility for the accuracy/completeness of this email and its attachments. _____________________________________________________________________ SOCNET is a service of INSNA, the professional association for social network researchers (http://www.insna.org). To unsubscribe, send an email message to [log in to unmask] containing the line UNSUBSCRIBE SOCNET in the body of the message.