[Air-L] CFP: #AoIR2017 Precon Workshop: Social Media Data Bootcamp and Research Hackathon

[Libby Hemphill]

Dear colleagues,

Please join us early in Tartu for a productive workshop collecting social
media data and planning projects!

https://aoir.org/aoir2017/preconworkshop/#SMD

Libby
Social Media Data Bootcamp and Research Hackathon

The technical expertise and computational resources required to collect and
manage large scale social media data exclude many researchers who have the
theoretical expertise to interrogate the data. Several tools have been
developed recently by researchers to address these problems, and we
introduce a few of those, and their developers, in this workshop.

This half-day workshop will help researchers interested in using data from
social media platforms get started collecting data and managing their data
workflow. We begin with brief overviews (roughly 10 minutes each) of
digital research practices (Rogers), big data research project management
(Hemphill), and open source tools for social media data collection (Hemsley
and Tanupabrungsun). The remainder of the workshop will be structured as a
research “hackathon” where participants will actively work in small groups
to articulate data needs for specific research projects, draft data
collection and management plans, and begin collecting data using existing
tools.

The organizers all have experience developing tools to facilitate the
capture of Internet data for a variety of research ends. They will each
introduce some of the available tools and will be on hand to help during
the hackathon. Rogers and colleagues have developed a suite of tools under
the Digital Media Initiative that facilitate data capture from sources such
as GitHub, Instagram, Pinterest, and Tumblr. Hemphill’s lab has developed a
project management approach for handling big social data research projects
and is involved in building infrastructures for social media data sharing.
Hemsley and Tanupabrungsun have developed the Social Media Tracker,
Aggregator, and Collector Toolkit that helps researchers quickly spin up
data collection projects for Twitter and Facebook.

While most of the workshop will focus on data tools and their use, we will
also discuss the theoretical and methodological challenges that big social
data present. For instance, we will discuss the limitations that platforms
place on data available through their APIs, the ethical considerations of
“public” data, and the potential for data sharing infrastructures to
facilitate social media research.

*Call for Applications*

We invite participants with a range of expertise studying social media to
submit applications. The workshop will be most useful for researchers who
have projects or questions in mind but who are unsure about how to get the
data they need to answer their questions.

Applications should be 300-600 words and should provide the following:

1. A short statement about their experience as a social media researcher –
along with research questions, projects, publications, etc.
2. An overview of the research project they would like to work on during
the hackathon. This overview should include the specific questions they are
addressing and the data challenges they are facing.
Because we hope to achieve measurable progress on each participant’s
research, we will limit the workshop to no more than 20 participants. We
may select up to 20 “observers” who will be invited to attend but whose
projects will not be a focus of the hackathon portion.

Applications should be submitted via Dropbox Requests
<https://www.dropbox.com/request/RFooIrvLPtaHBv1GZ1EF> by June 30, 2017 at
5pm CDT. All those who submit proposals will be notified of the status of
their applications before the August 1, 2017 Early Registration
<https://aoir.org/aoir2017/registration/> deadline. Please make sure your
name, email, and institutional affiliation are included in the application
you submit so that we can get in touch with you.

*Links to Tools*
https://wiki.digitalmethods.net/Dmi/ToolDatabase
http://www.casmlab.org/pipeline-process/
https://github.com/OCDX
https://github.com/bitslabsyr/stack