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A reminder that regular registration for #Sunbelt2016 is now open,
including workshop registration, at
http://insna.org/sunbelt2016/registration/. The deadline for workshop
registration is March 7th, 2016.
This is a workshop that I'm teaching for the 4th time at a Sunbelt/EUSN
conference. Please don't hesitate to forward this email or contact me if
you'd like more info.
(Apologies for cross-posting.)
*Introduction to ego-network analysis with R*
*Session Time:* Tuesday, April 5, 2016 - 3pm
*Workshop Length:* 2 sessions (6 hours)
*Attendance Limit:* 30
*Instructor:* Raffaele Vacca, University of Florida | [log in to unmask] |
*Workshop webpage:* www.raffaelevacca.com/teaching/workshops/ego-network-r/
*How to register:* http://insna.org/sunbelt2016/registration/
-- Short introduction to ego-network research and data.
-- Data structures for ego-networks in R: vectors, data frames and lists.
-- Network objects in R.
-- The split-apply-combine strategy: creating ego-level summary variables.
-- Looping over multiple ego-networks (for, while, repeat loops).
-- Writing your own R functions.
-- Applying your functions to multiple ego-networks: The “apply” family
of functions (apply, lapply, sapply, etc.).
-- The plyr package for easier split-apply-combining.
A laptop with RStudio installed. More details will be emailed to
participants before the workshop.
This workshop offers an introduction to ego-network analysis with R,
presenting essential facilities available in R to store and manipulate
ego-network data, to visualize ego-networks, and to perform
compositional and structural analysis on large collections of ego-networks.
The central idea behind ego-network analysis is that the people (alters)
that an individual (ego) knows, and the way that these people interact
with each other, affect outcomes in that individual’s life such as
mental wellbeing, smoking behavior, or assimilation to a foreign
culture. A typical ego-network study involves identifying a sample of
focal individuals (the egos), and collecting a network of personal
contacts (the alters) from each. Ego is asked about characteristics of
each alter, characteristics of each ego-alter relation, and
characteristics of alter-alter relations. This information is then
frequently aggregated into ego-level variables that summarize
ego-network characteristics, which can subsequently be linked to other
ego attributes and outcomes.
Typical ego-network analysis requires handling dozens or hundreds of
datasets, each representing one ego-network with ego attributes, alter
characteristics, and alter-alter ties. The analysis involves running the
same set of operations on each dataset, e.g. to extract compositional
and structural summary variables on each ego-network; and joining the
resulting metrics into a single dataset, together with other ego-level
or alter-level variables. This has been called the split-apply-combine
process in data analysis, in which raw data are split into pieces (in
this case, each piece representing one ego), the same analysis is
applied on each piece, and results are then combined together into a
Handling the split-apply-combine process in traditional point-and-click
software for statistical analysis is inefficient. Pointing and clicking
is repetitive, boring and prone to errors. It typically does not allow
users to run the same set of operations on many objects in batch,
without the user’s intervention. Perhaps more importantly, pointing and
clicking makes research not reproducible. R overcomes these limitations
and opens up a whole different way of doing ego-network analysis. It
eliminates pointing-and-clicking entirely, and allows users to write
reproducible scripts that batch analyze hundreds or thousands of
ego-networks simultaneously in few seconds.
This workshop will use real-world ego-network data, in combination with
the main R packages for network analysis (igraph and statnet). The
workshop can be taken as an introduction to the workshop “Simplifying
ego-centered network analysis in R with egonetR” by Till Krenz and
Andreas Herz. Students interested in a general introduction to social
network analysis with R should also consider taking the workshop “Using
R and igraph for Social Network Analysis" by Michal Bojanowski.
* 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
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