***** To join INSNA, visit http://www.insna.org ***** Dear colleagues, we have SNA courses available in sunny Manchester over the summer. Come and join us for two weeks of SNA and fun! methods@manchester Summer School 1-12 July 2019 University of Manchester Limited PhD Bursaries Available methods@manchester is delighted to be holding its annual Summer School from 1-12 July 2019. The Summer School offers a range of specialised courses covering a variety of topics that are particularly relevant to postgraduate and ECR research in humanities. The selection includes software training as well as qualitative and quantitative analysis. The course content is based on approaches from across the various schools in the Faculty of Humanities at the University of Manchester. Each Summer School course will run for one week, delivering four days of content to a five-day timetable (Monday afternoon to Friday lunch-time), building on successful methods@manchester and CMIST short-courses given throughout the year. Bursaries We have a small number of subsidised places for PhD students, reducing the cost of a course to £300*. To apply or for further details please email contact [log in to unmask]<mailto:[log in to unmask]> for an application form confirming the course you are applying for. *with the exception of Introduction to Longitudinal Data Analysis using R which will be reduced to £375. Available courses: * Creative approaches to qualitative research (1-5 July 2019) * Introduction to Social Network Analysis using UCINET and Netdraw (1-5 July 2019) * Getting started in R: an introduction to data analysis and visualisation (1-5 July 2019) * Generalized linear models: a comprehensive system of analysis and graphics using R and the Rcommander (1-5 July 2019) * Research Methods in Political Economy (1-5 July 2019) * Introduction to Arc Pro (8-12 July 2019) * Introduction to longitudinal data analysis using R (8-12 July 2019) * Advanced social network analysis (8-12 July 2019) * Data Visualisation (8-12 July 2019) * Quantitative policy evaluation (8-12 July 2019) Further information on the SNA courses is set out below. Bursary applications may be made to [log in to unmask]<mailto:[log in to unmask]> Full details about the methods@manchester Summer School are available at the methods@manchester website<https://urldefense.proofpoint.com/v2/url?u=https-3A__www.methods.manchester.ac.uk_connect_events_summer-2Dschool-2D2019_&d=DwIF-g&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=uXI5O6HThk1ULkPyaT6h2Ws3RKNKSY__GQ4DuS9UHhs&m=TVTtUhjo27dAeF43DONRo58LXIFR7Ut1eHiJSJHtvIc&s=TkS93SK3LzdawF9HlEJIg6ve8PJuZ-6mjeYiknU7ZTY&e=>. • Introduction to Social Network Analysis using UCINET and Netdraw (1-5 July 2019) This 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, visualisation, 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 on the use of UCINET software and will give participants the experience of analysing real social network data using the techniques covered in the workshop. No prior knowledge of social network analysis is assumed for this course. • Advanced social network analysis (8-12 July 2019) An introduction to statistical analysis of networks and some advanced concepts building on the introductory course. 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 for cross-sectional data. 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 the analysis of networks using exponential random graph models (ERGM) and permutation tests. 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 [TS1] and R as well as other specialist sna software Eg Visone and UCINET. In R we will learn how to use the packages ‘sna’ and ‘statnet’. No familiarity with R is assumed but preparatory exercises will be provided ahead of the course. Methods@Manchester Tel: 0161 275 4269 https://urldefense.proofpoint.com/v2/url?u=https-3A__www.methods.manchester.ac.uk_&d=DwIF-g&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=uXI5O6HThk1ULkPyaT6h2Ws3RKNKSY__GQ4DuS9UHhs&m=TVTtUhjo27dAeF43DONRo58LXIFR7Ut1eHiJSJHtvIc&s=WXqYPFwHKEFBWEMOtp4fxEskPFVhZ_yWSixE1hYmGt8&e= Elisa Bellotti Senior Lecturer Sociology Programme Director New publications * Bellotti, E., Spencer, J., Lord, N. & Benson, K. "Counterfeit Alcohol Distribution: A Criminological Script Network Analysis". In European Journal of Criminology. * Bellotti, E. “Scientific Networks.” In Oxford Bibliographies in Sociology. Ed. Janeen Baxter. New York: Oxford University Press Department of Sociology and Mitchell Centre for Social Network Analysis https://urldefense.proofpoint.com/v2/url?u=http-3A__www.socialsciences.manchester.ac.uk_research_research-2Dcentres-2Dand-2Dnetworks_mitchell-2Dcentre_&d=DwIF-g&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=uXI5O6HThk1ULkPyaT6h2Ws3RKNKSY__GQ4DuS9UHhs&m=TVTtUhjo27dAeF43DONRo58LXIFR7Ut1eHiJSJHtvIc&s=FrXoTnYchMSEaRTGfNvL_jHf10e80lvSMIVj-ObYKW4&e= University of Manchester Arthur Lewis Building Room 3.029 Bridgeford Street Manchester M13 9PL +44(0)1612752512 ________________________________ To unsubscribe from the SNA list, click the following link: https://urldefense.proofpoint.com/v2/url?u=https-3A__www.jiscmail.ac.uk_cgi-2Dbin_webadmin-3FSUBED1-3DSNA-26A-3D1&d=DwIF-g&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=uXI5O6HThk1ULkPyaT6h2Ws3RKNKSY__GQ4DuS9UHhs&m=TVTtUhjo27dAeF43DONRo58LXIFR7Ut1eHiJSJHtvIc&s=ox6TMScrbh-QrnF1JEo1pIQSG6qdLnSUEaN_XTglTb4&e= _____________________________________________________________________ SOCNET is a service of INSNA, the professional association for social network researchers (http://www.insna.org). 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