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Hamburg, Germany, 21 – 26 May, 2013
Sunbelt XXXIII
Workshop Program
Photo: www.mediaserver.hamburg.de, C. Spahrbier
Workshop Fees
INSNA has set the fee for all workshops:
Students: 30$ for a 3-hour workshop
60$ for a 6-hour workshop
INSNA members: 50$ for a 3-hour workshop
100$ for a 6-hour workshop
Affiliate members*: 50$ for a 3-hour workshop
100$ for a 6-hour workshop
* Please note that Affiliate Members are not eligible to submit data to the website; submit workshops /abstracts for consideration at the Sunbelt Conference or obtain Social Networks Journal subscription discounts.
Please check this document from time to time for any updates.
Workshop Overview [The number listed to the left of the workshop is the order of presentation for workshop descriptions that follow]
No. Workshop Title Workshop-Instructor(s) Date & Time
Tue: May 21, 2013
Wed: May 22, 2013
30 Introduction to Social Network Analysis Paola Tubaro Tue 3-6 and Wed 8-11
8 Introduction to UCINET and NetDraw Rich DeJordy Tue 11.30-2.30 and 3-6
13 Advanced Social network Analysis using UCINET and Netdraw Martin Everett &Steve Borgatti Wed 8-11 and 11.30-2.30
3 Analysis of large networks with Pajek Vladimir Batagelj & Andrej Mrvar Tue 3-6
25 Mesa Hispana for Social Networks Analysis Alejandro Arnulfo Ruiz Leon & Nina
Inez Jung
Tue 11.30-2.30 (and 3-6)
4 Introduction to Social Network Analysis with R Michał Bojanowski Tue 8-11 and 11.30-2.30
2 Introduction to Social Network Analysis with R and statnet Ryan Acton & Lorien Jasny Tue 8-11
14 Moving Beyond Descriptives: Basic Network Statistics with statnet Lorien Jasny & Ryan Acton Tue 11.30-2.30
9 Exponential-family Random Graph Modeling (ERGMs) with statnet Statnet Development Team Tue 3-6
23 Exponential random graph models for social networks, using Pnet Garry Robins Tue 8-11 and 11.30-2.30
15 Valued Network Modeling with statnet Pavel Krivitsky & Carter Butts Wed 11.30–2.30
7 Modeling Relational Event Dynamics with statnet Carter Butts & Christopher Marcum Tue 11.30-2.30
11 STERGM - Separable Temporal ERGMs for modeling relational
dynamics over time with statnet
Statnet Development Team Wed 8-11
10 Extending ERGM Functionality within statnet:
Building Custom User Terms
Statnet Development Team Wed 11.30–2.30
31 Social Network Approaches for Behavior Change Thomas Valente Wed 8-11
6a visone. Part I: Introduction Ulrik Brandes & Jürgen Lerner Wed 8-11
6b visone. Part II: Longitudinal Networks Ulrik Brandes & Jürgen Lerner Wed 11.30-2.30
28 Analysis of Longitudinal Social Network Data using SIENA Tom Snijders Tue 11.30-2.30 and 3-6
29 Advanced R Siena users’ workshop Tom Snijders Wed 11.30-2.30
21 Dynamic Network Analysis (DNA) and ORA Juergen Pfeffer & Kathleen M. Carley Tue 3-6 and Wed 8-11
20 tnet: Analysis of weighted, two-mode, and longitudinal networks Tore Opsahl Tue 8-11
22 multiplex: An R package for the analysis of multiple social networks Antonio Rivero Ostoic Wed 11.30-2.30
1 Hyperlink Network Analysis with VOSON Robert Ackland Wed 8-11 and 11.30-2.30
18 Sci2 - A Tool for Science of Science Research and Practice Ann McCranie Tue 8-11
5 Spatializing Social Networks: Methods for Integrating SNA and GIS Joana Borrero Luz Tue 8-11
12 Mixed Methods Research Designs for Ego-centered Social Networks Silvia Dominguez & Betina Hollstein Tue 3-6 and Wed 8-11
27 Net-Map: Collecting social network data and facilitating network
learning through participatory influence network mapping
Eva Schiffer & Jennifer Hauck Wed 11.30-2.30
16 Qualitative and quantitative network analysis: Triangulation with
VennMaker
Michael Kronenwett & Markus
Gamper
Tue 3-6 and Wed 8-11
19 Advanced Network Analysis and Targeting: A meta-network
approach to identifying organizational risk and conducting ethical
targeting
Ian McCulloh & Helen Armstrong Tue 8-11 and 11.30-2.30
24 Strategies to analyse social networks with email data Francisco Rodriguez Tue 8-11
26 Studying Human Behavior on Twitter Derek Ruths Tue 8-11 and 11.30-2.30
17 Working with Animal Social Networks and Encouraging
Collaborations between Animal Ecologists and Network Scientists
Jessica Kropczynski & Joseph Johnson Wed 11.30-2.30
Robert Ackland
Australian National University
LIMITED to 20 Seats
This course will provide students with an introduction to empirical approaches for studying WWW hyperlink networks, with a focus on
organisational hyperlink networks and blog networks. The practical part of the course will involve the use of VOSON (http://voson.anu.edu.au,
http://www.uberlink.com), which is a tool for hyperlink network construction and analysis, and is available as a web application and as a plugin
to NodeXL (a free Excel 2007/2010 template for social network analysis).
1 Hyperlink Network Analysis with VOSON Schedule
May 22, 2013
Part 1 - Wed 8-11 am
Part 2 – Wed 11.30-2.30
Pricing (US $)
Regular: $ 100
Student: $ 60
2 Introduction to Social Network Analysis with R and statnet Schedule
May 21, 2013
Tue 8-11 am
Pricing (US $)
Regular: $ 50
Student: $ 30
Ryan Acton & Lorien Jasny
University of Massachusetts Amherst
LIMITED to 30 Seats
This workshop session will serve as a basic introduction to the importation, manipulation, and descriptive analysis of social network data within
the R/statnet platform. Topics covered will include: an overview of basic R functions and data types; importation of network data into R;
network data manipulation; management of metadata for complex networks; visualization of network data; calculation of network descriptives
(e.g., centrality scores, graph-level indices); and use of classical network analytic techniques (e.g., blockmodeling). No prior experience with R or
statnet is assumed, but attendees should have familiarity with the basic concepts of descriptive network analysis. (Participation in this workshop
session is recommended prior to the other statnet sessions.)
statnet is a collection of packages for the R statistical computing system that supports the representation, manipulation, visualization, modeling,
simulation, and analysis of relational data. statnet packages are contributed by a team of volunteer developers, and are made freely available
under the GNU Public License. These packages are written for the R statistical computing environment, and can be used with any computing
platform that supports R (including Windows, Linux, and Mac). statnet packages can be used to handle a wide range of simulation and analysis
tasks, including support for large networks, statistical network models, network dynamics, and missing data.
3 Analysis of large networks with Pajek Schedule
May 21, 2013
Tue 3-6 pm
Pricing (US $)
Regular: $ 50
Student: $ 30
Vladimir Batagelj & Andrej Mrvar
University of Ljubljana
LIMITED to 30 Seats
In September 2011 a 64-bit version of Pajek 2.05 and in October 2011 a compact version Pajek-XXL became available. In April 2012 Pajek 3.01
with reorganized menu structure appeared. Besides this several new network analysis and visualization procedures (modularity of partition,
Louvain communities, pivot MDS, VOS, incidence matrix, etc.) were implemented in Pajek.
The 64-bit version of Pajek enables us to use all the available memory on 64-bit computers thus making possible the analysis of networks with
hundreds of millions of vertices.
In the workshop the new capabilities of Pajek will be presented and illustrated with applications in analysis of different large networks.
4 Introduction to Social Network Analysis with R Schedule
May 21, 2013
Part 1 - Tue 8-11 am
Part 2 - Tue 11.30-2.30
Pricing (US $)
Regular: $ 100
Student: $ 60
Michał Bojanowski ICM, University of Warsaw
LIMITED to 30 Seats
The workshop is an introduction to network data and classical SNA methods using R. It is planned to be a good prerequisite for other R-related
workshops, for example statnet/ERGM workshops, RSiena, tnet, and perhaps others.
The workshop is targeted especially towards people who have limited or no experience with R but have basic knowledge of Social Network
Analysis.
The first part of the workshop will introduce R itself. Participants will learn how to work with RStudio, R script files, data objects, and perform
basic data manipulation, visualization, and regression modeling.
The second part will focus on working with network data using R packages: igraph, network, intergraph, and preparing network data for analysis
with RSiena. The material will cover (1) manipulating network objects (2) working with node and tie attributes, (3) creating network
visualizations, (4) computing various classical SNA descriptives.
The workshop will be a balanced mixture of presentation and practical demonstrations of using R for Social Network Analysis. The participants
are encouraged to bring their own laptops.
One of the features of R is its reliance on script files and the lack of graphical user interface, although recently developed RStudio
(http://www.rstudio.org) bridges that gap. Nevertheless, the participants should be ready to follow a discussion that necessarily involves
learning R syntax.
5 Spatializing Social Networks: Methods for Integrating SNA and GIS Schedule
May 21, 2013
Tue 8-11 am
Pricing (US $)
Regular: $ 50
Student: $ 30
Joana Borrero Luz
Institut national de la recherche scientifique
LIMITED to 20 Seats
Since people and organisations are spatially embedded, research on social networks may require an understanding of the spatial dimensions of social
networks. For such research, impending questions may emerge: How are the actors in my network situated in space? How can I analyse the correlation
between social clusters and spatial clusters? How can I map measures of network centrality and equivalence within determined geographical spaces?
Current Social Network Analysis methods and software do not offer the tools necessary for integrating, visualising and analysing the spatial dimensions
of social networks. The common use of mathematics and statistics makes it nonetheless possible (and relatively easy) to integrate social network and
spatial information, and analyse and visualise the information through the combined use of Social Network Analysis and Geographic Information
System software.
The workshop will be structured in a manner that can respond to the specific needs and questions of participants during the workshop. The purpose is
to equip participants with the basic tools they need to pursue the exploration of social and spatial network analysis within their own fields of interest.
The first part of the workshop will be an introduction to GIS and the language of spatial analysis. We will explain the common use of mathematics and
statistic in SNA and GIS, and how this may facilitate the integration of social network and spatial analysis. The second part of the workshop will be a
hands-on application of methods for the spatial analysis of social network data. During the training, participants have access to data sets prepared
specifically for the workshop and will be asked to perform exercises with the data (if computers and software are available).
This workshop is meant to be a dynamic introduction to the use of Geographic Information Systems in studies on social networks. Participants are
expected to be familiar with Social Network Analysis and have some knowledge of statistical methods. A folder containing the following documents will
be distributed to all participants: 1) summary of the workshop; 2) step-by-step guide for all procedures explained during the workshop; 3) list of
bibliographical references; and 4) short article illustrating the use of GIS for Social Network Analysis.
6 visone. Part I: Introduction
visone. Part II: Longitudinal Networks
Schedule
May 22, 2013
Part 1: Wed 8-11 am
Part 2: Wed 11.30-2.30
Pricing (US $)
Regular: $ 100
Student: $ 60
Part 1 or 2 only
Regular: $ 50
Student: $ 30
Ulrik Brandes & Jürgen Lerner
University of Konstanz
Part 1 is LIMITED to 50 Seats
Part 2 is LIMITED to 30 Seats
visone (ital. mink) is a free software tool that combines comprehensive means for analysis with unique visualization capabilities. It can also be
used as a graphical frontend to R, RSiena, and KNIME.
Part I: Introduction.
This is a hands-on introduction to visone. After a brief overview of its design and features, we will explore some of its core functionality. Using
exemplary network analyses, we will produce presentations of findings step-by-step, starting from data input to arrive at publication quality
information visualizations.
Part II: Longitudinal Networks.
This part is suitable for users already familiar with the basic functionality of visone, and preferably also the RSiena software for stochastic actor-
oriented models. We will create time-coherent animations of longitudinal networks and use graphical means to assess specifications of network
evolution models.
It is advisable to bring a laptop running Windows, MacOS, or Linux. The software is written in Java and easily installed from www.visone.info. It
features many standard and non-standard methods for analysis and visualization of networks, and a powerful graphical user interface. It's native
file format is GraphML, allowing for arbitrarily many attributes of nodes, links, and networks, but other formats such as CSV tables, UCINet DL,
Pajek .net, etc., can be imported. Visualizations can be exported as pdf, png, tiff, svg, or Windows metafiles.
7 Modeling Relational Event Dynamics with statnet Schedule
May 21, 2013
Tue 11.30-2.30
Pricing (US $)
Regular: $ 50
Student: $ 30
Carter Butts & Christopher Marcum
University of California, Irvine
LIMITED to 30 Seats
This workshop session will provide an introduction to the analysis of relational event data (i.e., actions, interactions, or other events involving
multiple actors that occur over time) within R/statnet platform. We will begin by reviewing the basics of relational event modeling, with an
emphasis on models with piecewise constant hazards. We will then discuss estimation of dyadic and more general relational event models using
the relevent package, with an emphasis on hands-on applications of the methods and interpretation of results. Using the informR package, we
will then show how to construct models for spell data, and data involving multiple event types. Attendees are expected to have had some prior
exposure to R and statnet, and completion of the "Introduction to Network Analysis with R and statnet" workshop session is suggested (but not
required) as preparation for this session. Familiarity with parametric statistical methods is strongly recommended, and some knowledge of
hazard or survival analysis will be helpful.
statnet is a collection of packages for the R statistical computing system that supports the representation, manipulation, visualization, modeling,
simulation, and analysis of relational data. statnet packages are contributed by a team of volunteer developers, and are made freely available
under the GNU Public License. These packages are written for the R statistical computing environment, and can be used with any computing
platform that supports R (including Windows, Linux, and Mac). statnet packages can be used to handle a wide range of simulation and analysis
tasks, including support for large networks, statistical network models, network dynamics, and missing data.
8 Introduction to UCINET and NetDraw Schedule
May 21, 2013
Part 1 – Tue 11.30-2.30
Part 2 – Tue 3-6 pm
Pricing (US $)
Regular: $ 100
Student: $ 60
Rich DeJordy
Northeastern University
LIMITED to 30 Seats
A beginner’s tutorial on the concepts, methods and data analysis techniques of social network analysis. The workshop begins with a general
introduction to the distinct goals and perspectives of network analysis, followed by a practical discussion of network data, covering issues of
data collection, data entry, visualization of datasets, transformation of datasets and mathematical/computer representation using UCINET and
NetDraw. We then discuss the interpretation and calculation of the most common measures of network centrality. An important element of this
workshop is that all participants obtain hands-on experience working with UCINET 6 for Windows and NetDraw visualization software. In order
to participate fully in the workshop, each participant should bring a Windows laptop computer (or Mac with a Windows emulator) to follow
along and gain hands-on experience running the analyses as they are being demonstrated by the instructors.
9 Exponential-family Random Graph Modeling (ERGMs) with statnet Schedule
May 21, 2013
Tue 3-6 pm
Pricing (US $)
Regular: $ 50
Student: $ 30
Statnet Development Team
U of Washington, UC Irvine, Penn State, UCLA
LIMITED to 30 Seats
This workshop provides a introductory tutorial on exponential-family random graph models (ERGMs) for social networks, emphasizing a hands-
on approach to fitting these models to empirical data. This session will provide a hands-on tutorial to ERGM modeling within the R/statnet
platform. The ERGM framework allows for the parametrization, fitting, and simulation from models that incorporate the complex dependencies
within relational data structures, and provides an extremely general and flexible means of representing them.
Topics covered within this session include: an overview of the ERGM framework; defining and fitting models to empirical data; interpretation of
model coefficients; goodness-of-fit and model adequacy checking; simulation of networks using ERG models; degeneracy assessment; and
modeling and simulation of complete networks from egocentrically sampled data. Attendees are expected to have had some prior exposure to
R, but extensive experience is not assumed.
Prerequisites: Familiarity with basic descriptive network concepts and statistical methods for network analysis within the R/statnet platform is
recommended. Attendees are expected to have had some prior exposure to R, but extensive experience is not assumed. The workshops
"Introduction to Network Analysis with R and statnet" and "Basic Network Statistics with statnet" are recommended as preparation.
statnet is a collection of packages for the R statistical computing environment that supports the representation, manipulation, visualization,
modeling, simulation, and analysis of network data. statnet packages are contributed by a team of volunteer developers, and are made freely
available under the GNU Public License. statnet packages can be used with any computing platform that supports R (including Windows, Linux,
and Mac), and they support statistical analysis of large networks, longitudinal network dynamics, and missing data.
10 Extending ERGM Functionality within statnet:
Building Custom User Terms
Schedule
May 22, 2013
Wed 11.30–2.30
Pricing (US $)
Regular: $ 50
Student: $ 30
Statnet Development Team
U of Washington, UC Irvine, Penn State, UCLA
LIMITED to 30 Seats
Exponential-family random graph models (ERGMs) represent a powerful and flexible class of models for the statistical analysis of networks.
statnet is a software development project that includes a wide range of packages that support this modeling framework. The variables on the
right hand side of an ERGM equation are different from the covariates in more traditional statistical models because they must be coded up by
hand before they can be used in a model. statnet includes about 100 of the most commonly used terms in the ergm package; but if you want a
specific term that is not included in the list, you would need to code it up yourself. This workshop teaches participants how to do this.
We provide a hands-on tutorial on the template statnet package "ergm.userterms" that can be modified to create user-specific ERGM terms. It is
designed to make this process as straightforward as possible. We explain some of the internal workings of statnet that will help users develop
their own network analysis capabilities. The workshop will teach through examples in a tutorial paper and demonstrate each step in the practical
process. Participants work in small groups to code up their own ergm.userterms during the last part of the workshop.
Prerequisites: This workshop will assume familiarity with R, and the and ergm package in statnet. The "Exponential-family Random Graph (ERG
or p*). Modeling with statnet" workshop is recommended as preparation.
statnet is a collection of packages for the R statistical computing environment that supports the representation, manipulation, visualization,
modeling, simulation, and analysis of network data. statnet packages are contributed by a team of volunteer developers, and are made freely
available under the GNU Public License. statnet packages can be used with any computing platform that supports R (including Windows, Linux,
and Mac), and they support statistical analysis of large networks, longitudinal network dynamics, and missing data.
11 STERGM - Separable Temporal ERGMs for modeling relational dynamics
over time with statnet
Schedule
May 22, 2013
Wed 8-11 am
Pricing (US $)
Regular: $ 50
Student: $ 30
Statnet Development Team
U of Washington, UC Irvine, Penn State, UCLA
LIMITED to 30 Seats
This workshop will provide an introduction to the estimation and simulation of dynamic ERGMs in statnet. This workshop will cover the
statistical theory and methods for separable temporal ERGM modeling (STERGM) , and the associated diagnostics and visualization tools (NDtv)
available for dynamic networks in statnet. STERGM can be used for both estimation and simulation of dynamic network data. An example of
the type of "network movie" these tools can produce can be found at statnet.org/movies.
STERGMs can be estimated from both network panel data and cross-sectional, egocentrically sampled network data. Egocentrically sampled
network data are often collected in settings when other network sampling approaches are not practical. When the alter-specific questions
include retrospective information on the start and end of relationships, this can be treated as egocentric event history data. Such data can
support a basic but surprisingly rich class of models for dynamic network analysis, relying on the available marginal information on relationship
duration and cross-sectional network structure.
Prerequisites: This workshop will assume familiarity with R, and the network, SNA and ergm packages in statnet. The "Exponential-family
Random Graph (ERG or p*) Modeling with statnet" workshop is recommended as preparation.
statnet is a collection of packages for the R statistical computing environment that supports the representation, manipulation, visualization,
modeling, simulation, and analysis of network data. statnet packages are contributed by a team of volunteer developers, and are made freely
available under the GNU Public License. statnet packages can be used with any computing platform that supports R (including Windows, Linux,
and Mac), and they support statistical analysis of large networks, longitudinal network dynamics, and missing data.
12 Mixed Methods Research Designs for Ego-centered Social Networks Schedule
May 21 and May 22, 2013
Part 1 - Tue 3-6 pm
Part 2 - Wed 8-11 am
Pricing (US $)
Regular: $ 100
Student: $ 60
Silvia Dominguez & Betina Hollstein
Northeastern University & Universität Hamburg
LIMITED to 25 Seats
This workshop will be conducted in two parts. The first part we introduce social network qualitative research and the principles of mixed
methods research designs; we will review data collection and sampling procedures, analytical approaches, and triangulation strategies pointing
out advantages and challenges of this approach. Illustrations of the theoretical and methodological aspects are given by bringing a variety of
examples from sociological and demographic studies.
The second part is devoted to the presentation of concrete procedure to apply mixed methods in network research both at the level of data
collection and analysis. There will be four modules: a) introduction of different graphical instruments to collect network data for ego centered
networks and their strong and weak points b) quantitative and qualitative dimensions of network relationships c) the analysis of ego networks in
a mixed method perspective (type construction, generalization questions) d) participants will be asked to join in a specific exercise designed to
practice social networks in a mixed methods perspective.
The workshop will be conducted by Betina Hollstein and Silvia Dominguez who are working and publishing on social networks from qualitative
and mixed methods research for several years. They have also co-edited a book Mixed Methods Social Networks coming out with Cambridge
University Press.
In order to participate fully in the workshop, participants should read the papers which will be send to participants appr. two weeks before the
conference begins. There are no other prerequisites for the attending the workshop.
13 Advanced Social network Analysis using UCINET and Netdraw Schedule
May 22, 2013
Part 1 - Wed 8-11 am
Part 2 – Wed 11.30-2.30
Pricing (US $)
Regular: $ 100
Student: $ 60
Martin Everett &Steve Borgatti University of Manchester & LINKS/Kentucky
LIMITED to 30 Seats
This is a 6-hour workshop for participants who already have some experience with network analysis, but would like to learn more. We cover
advanced aspects of centrality, finding subgroups, and measuring equivalence. We also cover advanced techniques for analyzing network change
and handling multiple relations, missing data, non-symmetric data, valued data and 2-mode data. Throughout, we demonstrate
powerful,sometimes-undocumented features of UCINET and NETDRAW, including convenient ways of entering non-standard data. Note: what
makes this workshop ‘advanced’ is the selection of topics, not the speed or complexity of the exposition. In other words, wherever practical, all
concepts are explained from first principles, making as few assumptions about prior knowledge as possible. However, we do assume basic
familiarity with UCINET as a pre-requisite for the workshop. Attendees are assumed to have UCINET downloaded and running on their laptops.
14 Moving Beyond Descriptives: Basic Network Statistics with statnet Schedule
May 21, 2013
Tue 11.30-2.30
Pricing (US $)
Regular: $ 50
Student: $ 30
Lorien Jasny & Ryan Acton
University of California, Davis
LIMITED to 30 Seats
This workshop session will serve as an introduction to the use of basic statistical methods for network analysis within the R/statnet platform. The
session will focus on permutation tests for marginal relationships between node or graph-level indices and covariates in both one and two mode
networks; network correlation and regression; and exploratory multivariate analysis of multi-network data sets. Participants will gain an
understanding of the mechanics of these tests, the hypotheses they test, and how to use the functions in the SNA package. Attendees are
expected to have had some prior exposure to R, but extensive experience is not assumed. Completion of the "Introduction to Network Analysis
with R and statnet" workshop session is suggested (but not required) as preparation for this session. Familiarity with the basic concepts of
descriptive network analysis (e.g., centrality scores, network visualization) is strongly recommended.
statnet is a collection of packages for the R statistical computing system that supports the representation, manipulation, visualization, modeling,
simulation, and analysis of relational data. statnet packages are contributed by a team of volunteer developers, and are made freely available
under the GNU Public License. These packages are written for the R statistical computing environment, and can be used with any computing
platform that supports R (including Windows, Linux, and Mac). statnet packages can be used to handle a wide range of simulation and analysis
tasks, including support for large networks, statistical network models, network dynamics, and missing data.
15 Valued Network Modeling with statnet Schedule
May 22, 2013
Wed 11.30–2.30
Pricing (US $)
Regular: $ 50
Student: $ 30
Pavel Krivitsky & Carter Butts
Penn State University
LIMITED to 30 Seats
This workshop session provides a tutorial using statnet software ‘ particularly ergm and latentnet ‘ to model social networks whose ties have
weights (e.g., counts of interactions) or are ranks (i.e., each actor ranks the others according to some criterion), using latent space models and
exponential-family random graph models (ERGMs) generalized to valued ties, and emphasizing a hands-on approach to fitting these models to
empirical data.
The ERGM framework allows for the parametrization, fitting, and simulation from models that incorporate the complex dependencies within
relational data structures, and provides an extremely general and flexible means of representing them, while latent space models postulate an
unobserved social space in which actors are embedded, facilitating principled visualization and group detection. Topics covered within this
session include: importing, modifying, and exporting edge values on network objects; an overview of the valued ERGM framework and the
notion of reference distribution; an overview of latent space models for social networks; defining and fitting models to empirical data, including
ERGM terms meaningful for counts and ranks; interpretation of model coefficients; simulation of networks using these models; and ERGM
degeneracy assessment.
Prerequisites: Attendees are expected to have had some prior exposure to R, but extensive experience is not assumed. Familiarity with binary
ERG modeling with the R/statnet platform (e.g., from the "Exponential-family Random Graph (ERG) Modeling with statnet" workshop session) is
assumed.
statnet is a collection of packages for the R statistical computing system that supports the representation, manipulation, visualization, modeling,
simulation, and analysis of relational data. statnet packages are contributed by a team of volunteer developers, and are made freely available
under the GNU Public License. These packages are written for the R statistical computing environment, and can be used with any computing
platform that supports R (including Windows, Linux, and Mac). statnet packages can be used to handle a wide range of simulation and analysis
tasks, including support for large networks, statistical networks, valued networks, network dynamics, and missing data.
16 Qualitative and quantitative network analysis: Triangulation with
VennMaker
Schedule
May 21 and May 22, 2013
Part 1 - Tue 3-6 pm
Part 2 - Wed 8-11 am
Pricing (US $)
Regular: $ 100
Student: $ 60
Michael Kronenwett & Markus Gamper
University of Trier
LIMITED to 20 Seats
This workshop will introduce in ego-centered network analysis and how to combine qualitative and quantitative network analysis (triangulation)
with VennMaker. On the basis of short examples we show how to collect and analyze network data with this software tool. The participants
learn how to make (create) questionnaires for ego-centered networks and how to configure so called digital network maps. Digital networks
maps allow collecting network data on a visual level. In short exercises, the participants then carry out interviews with the program. Then we
show how the collected data can be exported in Excel, Pajek and SPSS. All participants will get a full version of VennMaker. More information
about this software is available at http://www.vennmaker.com
17 Working with Animal Social Networks and Encouraging Collaborations
between Animal Ecologists and Network Scientists
Schedule
May 22, 2013
Wed 11.30-2.30
Pricing (US $)
Regular: $ 50
Student: $ 30
Jessica Kropczynski & Joseph Johnson
Penn State University
LIMITED to 30 Seats
Researchers interested in animal behavior have long sought to better understand relationships between individual animals, as well as larger
social structures, in social animal species. Animal ecologists have been applying concepts of social network analysis for over a decade, but careful
examination of many studies reveals an incomplete understanding of many network analysis concepts and capabilities. This signifies a large
opportunity for network scientists to collaborate with animal ecologists to better combine these areas of expertise and generate meaningful
hypotheses and analyses regarding animal social networks. This workshop will be led by a team of scientists which come from each of these
disciplines and provide an example of how network analysis can used and misused in animal ecology. The workshop will focus on positive
examples of where network analysis can most meaningfully be applied in animal research, focusing not only on charismatic species which has
received ample attention (i.e., primates and cetaceans), but also focus on small mammals which are more common in wild as well as captive
settings (i.e., rodents and bats). The workshop will give an overview of possible study designs, highlighting common pitfalls, and allow attendees
to discuss their own research interests and ideas. Organizers will present data collected on free-ranging mammals to illustrate the types of data
commonly collected and help generate ideas for collaborations that attendees could forge in their regions. The workshop will emphasize the
diversity in data collection methods existing in the animal ecology field and encourage attendees to take advantage of this diversity and reach
out to ecologists in their area in order to foster the growth of social network analysis in animal ecology.
Please note: Participants are encouraged to bring a laptop with some type of network analysis software installed (preferably UCINET)
18 Sci2 - A Tool for Science of Science Research and Practice Schedule
May 21, 2013
Tue 8-11 am
Pricing (US $)
Regular: $ 50
Student: $ 30
Ann McCranie Indiana University Bloomington
LIMITED to 30 Seats
The Science of Science (Sci2) Tool is a modular toolset specifically designed for the study of science. It supports the temporal, geospatial, topical,
and network analysis and visualization of scholarly datasets at the micro (individual), meso (local), and macro (global) levels.
This workshop will provide an overview of the tools available in Sci2. Participants will also be able to follow along with several sample workflows
and datasets, including discussion of data gathering, preparation, and cleaning. Individuals with existing datasets that they would like to use with
Sci2 are encouraged to contact the instructor ahead of time.
Sci2 is an open source tool, freely available for download at http://sci2.cns.iu.edu. Development is supported in part by the Cyberinfrastructure
for Network Science Center and the School of Library and Information Science at Indiana University, the National Science Foundation, and the
James S. McDonnell Foundation.
19 Advanced Network Analysis and Targeting: A meta-network approach to
identifying organizational risk and conducting ethical targeting
Schedule
May 21, 2013
Part 1 - Tue 8-11 am
Part 2 - 11.30-2.30
Pricing (US $)
Regular: $ 100
Student: $ 60
Ian McCulloh & Helen Armstrong Curtin University
LIMITED to 30 Seats
Meta-networks offer a rich data source including many different relationships among actors, resources, knowledge, beliefs, and more. Social
networks are a subset of these networks. This workshop will expand traditional social network techniques, introducing techniques for analyzing
multi-level networks, non-social networks, and networks occupying differing relational contexts (online, face-to-face, transactional, etc.). The
use of relational algebra is demonstrated as a tool to extract multiple networks from limited relational data for further exploration. This
workshop will also present a review of key grounded theory in social network development to guide analysts through network analysis. Case
studies will be presented to demonstrate this approach applied to several knowledge-intensive organizations. Emphasis will be on
organizational consulting and organizational risk. Applications for military targeting and law enforcement will also be presented.
20 tnet: Analysis of weighted, two-mode, and longitudinal networks Schedule
May 21, 2013
Tue 8-11 am
Pricing (US $)
Regular: $ 50
Student: $ 30
Tore Opsahl Measr, Inc.
LIMITED to 30 Seats
tnet is a package written in R to serve three purposes:
1. Calculate social network measures on weighted datasets
Not everyone is the same. Some people are close to us, whereas others are just acquaintances. Few network measures, and fewer network
analysis programmes, can deal with datasets where the ties are differentiated by weights. By removing the weights of relations, we are removing
a lot of the richness within the dataset. This means that we are limiting the weight analysis to sensitivity analyses, which are difficult to interpret.
A close friendship is not the same as an acquaintance.
2. Calculate social network measures on two-mode
Most forms of interaction occur through mediums, such as meetings, projects, forums, etc. By simply joining two people if they have interacted
with the same medium, we greatly reduce the information available to analyse. For example, the clustering coefficient on a one-mode projection
of a two-mode network is meaningless as triangles are formed automatically when three or more people interact with the same medium. To
remove some of the biases that might invalidate the analysis, a new set of measures directed at analysing two-mode networks directly (and a
software were these measures are implemented) are needed.
3. Detect underlying principles that guide tie formation in datasets with time-stamped ties
Network analysis is often based on static networks. In these networks there are issues of dependence as everything depends on everything.
Therefore it is difficult to say why certain ties are created and others are not. In networks where the exact sequence of ties is known, the
endogeneity issue can be dealt with. This type of data is generally from online communities, email networks, and telephone networks (if your
dataset is not like this, but collected in waves, try Siena).
21 Dynamic Network Analysis (DNA) and ORA Schedule
May 21 and May 22, 2013
Part 1 - Tue 3-6 pm
Part 2 - Wed 8-11 am
Pricing (US $)
Regular: $ 100
Student: $ 60
Juergen Pfeffer & Kathleen M. Carley Carnegie Mellon University
LIMITED to 30 Seats
A lecture and hands-on workshop in which attendees learn about Dynamic Network Analysis (DNA) and the DNA toolkit ORA. Basic social network and dynamic
network representations, statistics, analysis and visualization techniques are covered, both in concept and practical operation. Foundational concepts and
techniques of Dynamic Network Analysis are presented including:
- Importing meta-network data from various sources (e.g., database, Social Media)
- Handling multiplex networks over time for multiple node classes including various node and link attributes
- Identification and reporting of key entities and groups using SNA and DNA metrics
- Accomplishing geo-spatial enabled network analysis and visualization
- Analyzing change of evolving networks over time
- Visualizing static and dynamic networks as well as geo-spatial networks
This full day session begins with an overview of ORA, and techniques for entering, visualizing, and analyzing social and meta-network data. How to identify key
entities and groups analytically and visually is then covered. Then we turn to how to assess networks over time and spatially. Spatial network metrics, trail and
geo-spatial visualization are highlighted. This workshop will be fast-paced and involves advanced material, however novices to network analysis should be able
to follow along, as the material is presented in an affable, but comprehensive manner. This is designed to be a non-technical workshop, however, by its very
nature the material will involve some mathematics, although this will be minimized as the delivery is driven towards forming an understanding of the concepts,
not mastery of the details. The material and its delivery are suitable for researchers and practitioners, alike.
The workshop focusses on ORA, which is a powerful network analysis tool, capable of handling large networks, and supporting meta-network data, geo-spatial
network data, and dynamic network data. Relatively unique features include handling of thousands of networks over time, trail and network visualization, fuzzy
grouping algorithms, multi-mode network assessment, built in network simulators, and powerful visualizer with data entry and mark-up capabilities.
Participants will be provided with a data CD containing the complete set of software, sample data, and a user’s guide, and will be guided through its installation
and subsequent hands-on usage.
Computer Equipment: The software presented in this tutorial is Windows operating system (32/64 bit) based. Participants with windows emulators should pre-
load and test the ORA software from the CASOS website ‘ http://www.casos.cs.cmu.edu/projects/ora/. Participants should bring their own laptops to the
workshop. Nevertheless, participants not able to bring a Windows-based laptop computer to the sessions are welcome to participate, and will still fully benefit
from the workshop. The software will be screen-projected to the group as a live walk-through demonstration.
22 multiplex: An R package for the analysis of multiple social
networks
Schedule
May 22, 2013
Wed 11.30-2.30
Pricing (US $)
Regular: $ 50
Student: $ 30
Antonio Rivero Ostoic
University of Southern Denmark
LIMITED to 20 Seats
'multiplex' is computer program written in R that is specially designed for the analysis of social networks made of different types of relations.
The program has effective ways to treat multiple networks data sets with routines that combine algebraic structures like the partially ordered
semigroup with the existing relational bundles found in multiple networks.
Among the functions available in 'multiplex' there is one that models the local role algebras based on the simple and compound relations of the
actors, and the role structure of the overall system as well. Another function finds the different relational patterns at the dyadic level in the
network which can serve for a further analysis applying structural theories. Besides, there is a procedure for the construction and analysis of
signed networks through the semiring structure. It is possible to take the actors attributes in the analysis, and in this way their network exposure
can be taken in the context of multiple networks, or else the attributes can be embedded in the relational structure.
The methodology of the workshop is learning by doing, and the package count with data sets that can be used as an example for the different
functions. Naturally, the participants are welcome to send or bring their own data sets to the workshop with the possibility to focus on particular
research problems.
23 Exponential random graph models for social networks, using Pnet Schedule
May 21, 2013
Part 1 - Tue 8-11 am
Part 2 – Tue 11.30-2.30
Pricing (US $)
Regular: $ 100
Student: $ 60
Garry Robins, Peng Wang, Johan Koskinen & Dean Lusher University of Melbourne, Australia, University of Manchester & Swinburne University of Technology
LIMITED to 30 Seats
This workshop is in conjunction with the release of a new text on ERGMs: Lusher, D., Koskinen, J., & Robins, G. (2012). Exponential random graph models for
social networks: Theory, methods and applications. Cambridge University Press.
The workshop will introduce and utilize PNet, simulation and estimation software for ERGMs, including the new software for multilevel networks, MPNet.
The general theoretical background to ERGMs will be reviewed, model formulation discussed, and simulation, estimation and goodness of fit procedures
presented. Meaningful interpretation of parameter estimates will be emphasized, as well as the importance of model goodness of fit. Social selection models
incorporating individual-level attributes will also be described. For those who bring laptops to the workshop, hands-on exercises using PNet will be included,
both in simulating networks and in fitting illustrative data sets. Extensions to models for multiple networks, bipartite networks and social influence processes
on networks may also be presented. New models for multilevel networks will be introduced, using MPnet.
Participants will be expected to have prior knowledge of fundamental social network concepts and terminology, and to have some knowledge of standard
statistical ideas (e.g. the notion of a statistical distribution, regression, logistic regression).
After completing the workshop we expect participants to:
- have a good understanding of the principles and aims of ERGM methodology;
- be aware of common obstacles and misconceptions with ERGMs;
- have a working handle on the workflow, from theoretical specification, technical specification and model fitting and interpretation and improvement;
- be familiar with and have a readied capacity for picking up extensions and more advanced topics;
- feel confident in being able to fit ERGMs to their own data
*PNet is freely available to participants (www.sna.unimelb.edu.au). Please note it is written for Windows PCs and may not function well under Mac or Linux
operating systems. (However, PNet usually works well in a non-native windows environment, such as parallels or boot camp.) Other Background Reading: Robins, G., Pattison, P., Kalish, Y., & Lusher, D. (2007). An introduction to exponential random graph (p*) models for social networks. Social Networks, 29, 173-191.
Robins, G.L., Snijders, T.A.B., Wang, P., Handcock, M., & Pattison, P. (2007). Recent developments in exponential random graph (p*) models for social networks. Social Networks, 29, 192
24 Strategies to analyse social networks with email data Schedule
May 21, 2013
Tue 8-11 am
Pricing (US $)
Regular: $ 50
Student: $ 30
Francisco Rodriguez
UNED
LIMITED to 20 Seats
During the workshop we will discuss about different possibilities to use email data to describe a social network and at the same time we will
speak about the problems that exist on the Data Acquisition - from the technological point of view but also accompanied from the syntax
problem. We will look for different scopes to face it.
Also a goal for that kind of analyses will be spoken.
At the end of the workshop, the participant will be able to give answers about strategies on how to gain information from email systems, which
kind of problems will be found and witch kind of information can be extract.
25 Mesa Hispana for Social Networks Analysis Schedule
May 21, 2013
Tue 11.30-2.30
plus satellite paper session: Tue 3-6 pm
Pricing (US $)
Regular: $ 50
Student: $ 30
Alejandro Arnulfo Ruiz Leon & Nina Inez Jung
Universidad Nacional Autonoma de Mexico
LIMITED to 30 Seats
The aim of this workshop is to provide a space for researchers from Iberoamerica interested in the network perspective to present their projects
in progress and join the international community at Sunbelt. The workshop is structured in two parts over two days: a presentation on networks
visualization using Pajek by the organizers (3 hrs.) and a brief presentation of papers by the participants (3 hrs.)
Please note: This workshop will be in the spanish language.
.
26 Studying Human Behavior on Twitter Schedule
May 21, 2013
Part 1 - Tue 8-11 am
Part 2 - 11.30-2.30
Pricing (US $)
Regular: $ 100
Student: $ 60
Derek Ruths
McGill University
LIMITED to 30 Seats
Since Twitter's creation in 2006, it has become one of the most popular microblogging platforms in the world. By virtue of its popularity, the
relative structural simplicity of Twitter posts, and a tendency towards relaxed privacy settings, Twitter has also become a popular data source for
research on a range of topics in sociology, psychology, political science, and anthropology. Nonetheless, despite its widespread use in the
research community, there are many pitfalls when working with Twitter data.
In this workshop, we will lead participants through the entire Twitter-based research pipeline: from obtaining Twitter data all the way
through performing some of the sophisticated analyses that have been featured in recent high-profile publications. Participants will leave with
able to independently collect Twitter data and analyze a wide array of social processes present in the data, from sentiment to social network
structure.
In the first section of the tutorial, we will cover the nuts and bolts of obtaining and working with a Twitter dataset including: using the
Twitter API, the firehose, and rate limits; strategies for storing and filtering Twitter data; and how to publish your dataset for other researchers
to use.
In the second section, we will delve into techniques for analyzing Twitter content. We will focus on several widely used techniques
including the measurement of mood and sentiment; entity extraction; and mention, retweet, and follower-based social network extraction.
Some time will also be given to more experimental techniques including latent attribute inference and topic classification. Throughout time will
be given to explain the theoretical basis for the methods, but the primary focus will be on showing participants how to do the various analyses.
We assume that participants will have little to no prior experience with mining Twitter or other social network datasets. As the
workshop will be interactive, participants are encouraged to bring a laptop. Code examples and exercises will be given in Python, thus
participants should have some familiarity with the language. However, all concepts and techniques covered will be language-independent, so
any individual with some background in scripting or programming will benefit from the workshop.
27 Net-Map: Collecting social network data and facilitating network
learning through participatory influence network mapping
Schedule
May 22, 2013
Wed 11.30-2.30
Pricing (US $)
Regular: $ 50
Student: $ 30
Eva Schiffer & Jennifer Hauck
World Bank
LIMITED to 20 Seats
Net-Map is a low-tech, low-cost, interview-based mapping tool that combines the mapping of multiplex networks with actor analyses and an in-
depth qualitative discussion of the network. As a research tool it delivers quantitative network data, an assessment of the influence, goals and
roles of the actors (independent of their centrality) and rich qualitative data which digs deeper into the questions ‘How?’ and ‘Why?’. Further,
the tool can be used for group facilitation, strategic planning, conflict resolution and change management, as it allows groups to engage in
productive discussions about the complexity of a problem, structural reasons for success and failure, bottlenecks and windows of opportunities.
The goal of this hands-on workshop is to briefly introduce the Net-Map method and some case study examples, before the participants will map
out their own case studies and in the process learn how to develop an appropriate question, facilitate the interview and ‘read’ and discuss the
resulting map.
The workshop is open to everybody, but could be of special interest for researchers involved in participatory and applied research. It does not
require previous experience with social network analysis.
28 Analysis of Longitudinal Social Network Data using SIENA Schedule
May 21, 2013
Part 1 - Tue 11.30-2.30
Part 2 - Tue 3-6 pm
Pricing (US $)
Regular: $ 100
Student: $ 60
Tom Snijders
University of Oxford and University of Groningen
LIMITED to 30 Seats
This workshop is about statistical inference for longitudinal observations on social networks. Longitudinal social network data are understood here as two or
more repeated observations of a directed graph on a given node set (usually between 30 and a few hundred nodes). The workshop teaches the statistical
method to analyze such data, for which a tutorial is given in Snijders, T.A.B., Steglich, C.E.G., and van de Bunt, G.G. (2010), Introduction to actor-based models
for network dynamics (Social Networks), and implemented in the RSiena program.
The statistical model is the actor-oriented model where the nodes are actors whose choices determine the network evolution. This allows to include various
network effects (reciprocity, transitivity, cycles, popularity, etc.), effects of individual covariates (covariates connected to the sender, the receiver, or the
similarity between sender and receiver), and of dyadic covariates.
An important extension is to have, in addition to the network, one or more actor variables that evolve in mutual dependence with the network; an example is a
friendship network of adolescents where drinking behavior is a relevant actor variable which influences, and is influenced by, the friendship network. This leads
to models for the simultaneous dynamics (‘co-evolution’) of networks and behavior, which are a special option in RSiena. Further information about this
method can be found at the SIENA website (see below).
The statistical analysis is based on many repeated Monte Carlo simulations of the network evolution model and therefore is a bit time-consuming. The
computer program RSiena is a package in the statistical computer system R. The workshop will demonstrate the basics of using RSiena. Attention will be paid to
the underlying statistical methodology, to examples, and to the use of the software.
The first session is intended for those without previous experience with this method, and will focus on the intuitive understanding of the model and operation
of the software. The second session will present models for the simultaneous dynamics of networks and behavior and other more advanced topics such as
model specification, multivariate networks, structurally determined values, and goodness of fit checking.
Participants are requested to check the SIENA website (Courses-activities tab) in the week before the workshop to download the workshop materials. For
optimal benefit, it is advisable to bring an own laptop with R and RSiena already installed, such that some steps of data manipulation and analysis can be
followed hands-on. Participants for whom R is new are requested to learn the basics of R before the workshop: how to run R and how to give basic R
commands. This is to reduce the amount of new material to digest at the workshop itself. The Siena website (RSiena tab) has some links which can be helpful
for this purpose: it’s not hard!
SIENA website: http://www.stats.ox.ac.uk/~snijders/siena
29 Advanced R Siena users’ workshop Schedule
May 22, 2013
Wed 11.30-2.30
Pricing (US $)
Regular: $ 50
Student: $ 30
Tom Snijders
University of Oxford and University of Groningen
LIMITED to 20 Seats
This workshop is intended for experienced users of RSiena, the package in the statistical software system R for analyzing longitudinal data of
networks, and of networks and behavior.
A number of new features of RSiena, and some possibilities that may be considered advanced options, will be discussed and demonstrated.
The following topics will receive attention:
‘ Goodness of fit checking with sienaGOF.
‘ Selection and Influence tables.
‘ Multilevel analysis of network dynamics.
‘ Dynamics of two-mode networks.
‘ Dynamics of multiple (multivariate) networks.
‘ Dynamics of networks with ordered categorical tie values.
‘ Depending on progress still to be made: the Settings model for dynamics of larger networks.
Participants are requested to check the SIENA website (Courses-activities tab) in the week before the workshop to download the workshop
materials. Participants might consider bringing their own laptop with R and RSiena installed, and these materials available, such that some steps
of the data analysis can be followed hands-on.
SIENA website: http://www.stats.ox.ac.uk/~snijders/siena
30 Introduction to Social Network Analysis Schedule
May 21 and May 22, 2013
Part 1 - Tue 3-6 pm
Part 2 - Wed 8-11 am
Pricing (US $)
Regular: $ 100
Student: $ 60
Paola Tubaro
University of Greenwich
LIMITED to 30 Seats
The workshop is aimed at researchers and post-graduate students who are new to social network analysis (SNA), and would like to better understand whether
and how they can use it to enhance their research programmes. The goal of the workshop is to provide attendees with basic insight into SNA, and how it can
be used in social science research, policy and business applications. Multiple examples from empirical research are provided, using both "classical" social and
organisational network data and web-based data. There are some simple computer-based exercises with Gephi for an hands-on illustration of how to visualize
different types of network data and how to compute basic metrics and indicators.
Participants will learn:
· Fundamental principles of SNA and their grounding in social theories;
· The use of network-based reasoning to draw social policy and business recommendations;
· Some essential technicalities: collection methods, format and properties of network data;
· Opportunities and challenges arising from the increasing availability of social network data from the Internet;
· Use of visualisation software packages and how they support network data interpretation;
· Basic measures of network composition and structure ‘ how they can be used to uncover important aspects of the social phenomenon under study and how
they can be represented graphically;
· A flavour of the usefulness of more complex statistical models of networks such as ERGM and Siena;
· How SNA can be successfully integrated into social science research, business applications and policy advice using various sources;
· What resources (books, journals, conferences) are available to support research in SNA.
Requirements: Participants may come from all social sciences backgrounds and are assumed to have no previous knowledge of Social Network Analysis.
Although the workshop does not focus on any specific software or data handling tool, it offers an opportunity for participants to have a first practical
experience of how to use social network data, draw graphs, and perform some simple calculations and analyses. Therefore, participants are advised to bring
their own laptop and to download Gephi, a free software for social network exploratory analysis and visualisation. Available at: http://gephi.org/
Learning Outcomes: The workshop will provide attendees with a basic insight into social network analysis and how it can be used in their social science,
business and policy research as well as applications.
31 Social Network Approaches for Behavior Change Schedule
May 22, 2013
Wed 8-11 am
Pricing (US $)
Regular: $ 50
Student: $ 30
Thomas Valente
University of Southern California
LIMITED to 30 Seats
This workshop introduces the many ways that social networks influence individual and network-level behaviors. It also provides a brief
introduction to analytic approaches for understanding network influences on behaviors. Then we review existing evidence for the utility of using
social network data for behavior change in a variety of settings including health behaviors and organizational performance. The workshop
presents a typology of network interventions and reviews existing evidence on the effectiveness of network interventions. (Students familiar
with the R environment may follow an R script written to demonstrate the 24 or so tactical interventions presented.) The workshop will be
conducted by Tom Valente who has been developing and implementing network based interventions for over 10 years. No pre-requisites.
