[ecrea] Digital Media Winter Institute 2018 (Lisbon) - Call for participation

Digital Media Winter Institute 2018

Universidade NOVA de Lisboa I UT Austin Portugal

Lisbon, Portugal


We are pleased to invite you to Digital Media Winter Institute 2018.


The Digital Media Winter Institute is dedicated to advancing the study
of new media, social media methods, and data visualization by
promoting the practice of interdisciplinary research through the
data-sprint approach and other intensive hands-on work courses. This
is an initiative of iNOVA Media Lab - Universidade NOVA de Lisboa /
NOVA FCSH, and supported by UT Austin I Portugal program.


The Digital Media Winter Institute 2018 offers two moments:

SMART Data Sprint: Interpreters of Platform Data

Image Networks: Automated Analysis of Visual Content


* * *

SMART Data Sprint: Interpreters of Platform Data
(http://inovamedialab.org/smart-data-sprint/)

29 January - 2 February 2018 I  9:30 - 17:30

The sprint will receive Bernhard Rieder (University of Amsterdam) and
Dhiraj Murthy (UT Austin) as keynote speakers and tutors of practical
labs.

Senior researchers, doctoral and masters students will also be leading
Practical Labs* that contemplate the following themes:

» Data Extraction Tools

» Working with tabular data

» Raw Graphs

» Visual content analysis with Image Plot

» Network Analysis

» Image Networks

The projects will contemplate public health issues (Zika Virus) and
Genre Studies (Femicide). Senior researchers from Brazil and Portugal,
and an Italian journalist are leading the projects. Participants are
also invited to pitch projects.


Deadline for applications: 8 January 2018


* * *

Image Networks: Automated Analysis of Visual Content
(http://inovamedialab.org/image-networks/)

5 – 8 February 2018 I 17:00 – 21:00

Limit of 20 participants


The course will present and discuss a set of methods and tools for
studying large visual datasets which are based in the recent
availability of cloud computing computer vision frameworks, dealing
specifically with the Google Vision API. Possibilities and limitations
of these techniques will be discussed, in addition to the learning of
their implementation in research practice.


Deadline for applications: 8 January 2018

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