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*****  To join INSNA, visit http://www.insna.org  *****

*What*: Two 3-hour workshops on ego-network analysis with R

*Where*: XXXV Sunbelt Conference of the International Network for Social 
Network Analysis (INSNA) – June 23 to June 28, 2015 – Brighton, UK - 
http://sunbelt2015.org

*When*: Tuesday June 23, 8am – 11am; 11:30am – 14:30pm

*Length*: Two 3-hour workshops. The two workshops are consecutive, 
however attendants can register for either one separately.

*Technology*: Attendants will need a laptop with R 
(http://cran.r-project.org) and R-Studio (www.rstudio.com) installed. 
The workshop will introduce the R package egonetR for ego-network data 
import and analysis.

*Background*: No previous familiarity with ego-network research is 
required. Some familiarity with R is an advantage, but not necessary.

*Cost*: Details on regular and student rates are available at 
http://insna.org/sunbelt2015/?page_id=831

More information is available at http://rego.tillt.net.

*1. Introduction to ego-network analysis with R (data collection and 
management)*
====================================================================
/Raffaele Vacca/, University of Florida
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Full abstract: http://insna.org/sunbelt2015/?page_id=746

This workshop will introduce attendants to ego-network research, with a 
special emphasis on research design and ego-network data types. We will 
cover the usage of R for the management of ego-network data, network 
visualization, and basic procedures to analyze the composition and 
structure of ego-networks. We will focus on the main facilities 
available in R to manage ego-network data and run ego-network analyses 
in batch: loops (for, while, repeat), the “apply” family of functions 
(apply, lapply, sapply, tapply, mapply), and the plyr package for the 
“Split-Apply-Combine” analysis strategy. We will use “igraph” and 
“network”, the two main packages for network analysis in R. The workshop 
is divided in two parts. A shorter introductory part will discuss 
ego-network research design and data, particularly as opposed to 
socio-centered network research. A subsequent, longer part will be a 
hands-on lab where participants will run R code on real-world data. This 
second part will use data and R code from actual ego-network research 
projects.

*2. Advanced ego-network analysis with R (analytical procedures)*
=================================================================
/Till Krenz/, Otto-von-Guericke University
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/Andreas Herz/, University of Hildesheim
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Full abstract: http://insna.org/sunbelt2015/?page_id=228

Ego-network analysis can be conducted at two different levels: the alter 
level (ego-alter-relationships) and the network level (structure of the 
overall ego-centered network). The first part of the workshop will 
introduce SNA measures at the alter level (e.g. multiplexity) and the 
network level (size, density, EI-Index, diversity, proportions of ties 
with specific attributes). A second part will treat multivariate 
analyses, both at the network level and the alter level. At the network 
level we focus on standard regression and cluster analysis. In standard 
regression analysis, network measures can be used as dependent or 
independent variables, just as any other characteristic of ego. With 
regression we can analyze if networks differ by gender or age, or we can 
ask if network characteristics explain differences in egos’ attributes. 
With cluster analysis we introduce a way to find groups of ego-networks 
with similar patterns in their network-level information. At the level 
of the analysis of ego-alter dyads we give an introduction to multilevel 
analysis. Multilevel analysis accommodates for the nested nature of 
alter-level data and enables an overall view on the statistical 
association among dyad attributes.

-- 
* Raffaele Vacca *
Research Assistant Professor
College of Nursing ∙ Clinical and Translational Science Institute ∙ 
Bureau of Economic and Business Research
University of Florida

✎ Ayers Medical Plaza, 720 SW 2nd Ave #150 ∙ Gainesville ∙ FL 32601
✆ +1 (352) 392-2908 x221 ∙ +1 (352) 273-6010
☞ florida.academia.edu/raffaelevacca
✉ [log in to unmask]

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