Hi all,
Really exciting new special issue on semantic media that may be of interest
to Wikipedia/Wikidata researchers. See below and let me know if you have
any questions! Abstract deadline is July 15.
All best,
Heather (and Andrew)
*---*
*Dr Heather Ford*
Associate Professor and Head of Discipline, Digital and Social Media
<https://www.uts.edu.au/future-students/communication/digital-and-social-media>
School of Communication
<https://www.uts.edu.au/future-students/communication/about-communication/welcome-school-communication>
, University of Technology, Sydney <https://www.uts.edu.au/> (UTS)
Affiliate: UTS Data Science Institute
<https://www.uts.edu.au/data-science-institute> | Associate: UTS Centre for
Media Transition
<https://www.uts.edu.au/research-and-teaching/our-research/centre-media-transition>
| Associate Member: UTS Centre for Research on Education in a Digital
Society
<https://www.uts.edu.au/research-and-teaching/our-research/centre-research-education-digital-society>
w: hblog.org / t: @hfordsa <http://www.twitter.com/hfordsa> / pronouns:
she/her
*University of Technology Sydney*
Faculty of Arts and Social Sciences
PO Box 123. Broadway NSW 2007 Australia
I acknowledge the Gadigal People of the Eora Nation and the Boorooberongal
People of the Dharug Nation upon whose ancestral lands our campuses now
stand. I pay respect to Elders past, present and emerging, acknowledging
them as the traditional custodians of knowledge for these lands.
*Call for Papers*
*Social Media + Society** Special Issue: Semantic Media*
*Editors: Andrew Iliadis and Heather Ford*
This special issue focuses on “semantic media,” which we define as media
technologies that primarily orchestrate and convey facts, answers,
meanings, and “knowledge” about things directly in media products, rather
than lead people to other sources. Search engines and virtual assistants
respond directly to questions based on textual or verbal searches (e.g.,
“Things to do in Philadelphia?” or “What is the capital of Israel?”). The
special issue is thus dedicated to the often-invisible ways (to the
non-specialist) that internet companies are now actively involved in
constructing “knowledge” about the world. Organizations like Apple, Google,
Microsoft, Facebook, and Amazon extract, curate, and store facts served to
users in new and emerging media products. Such processes have significant
implications for the politics of knowledge sharing in the future.
We seek papers that examine how design decisions “bake” these facts into
the apps and platforms people use daily while focusing on the
infrastructures dedicated to orchestrating and presenting this information.
The goal is to understand the technologies that will drive social and
political outcomes when large internet companies become a primary conduit
through which people directly acquire an understanding of facts about the
world. We also seek to understand how governments, nonprofit, and
nongovernmental organizations engage these media technologies. Semantic
media are less about searching for keywords and matches on different
websites that are then ranked for people to choose. Instead, they deal with
identifying and describing entities (things like people, products, and
places) and directing interactions with those entities (actions like
purchasing, scheduling, and contacting). How do semantic media identify
concepts and connect related information about them? How do companies and
organizations produce facts and organize the data? From where does the data
originate? What do these semantic processes mean for web users and
administrators? What types of gatekeeping or safety checks do companies and
organizations perform concerning these facts?
Today’s semantic media have a long history reaching back to the “Semantic
Web” project initiated by web inventor Tim Berners-Lee. Yet, media
researchers do not adequately cover how companies and organizations
implement semantic technologies on platforms relative to their central
role. These semantic technologies are in proprietary and open source
products, and extensive media platforms are now using them to provide facts
and represent knowledge to various publics. Google’s Knowledge Graph is a
database of facts that Google uses to provide quick answers to the public,
and such graphs are in use at other companies. At the same time, Wikipedia
has a product called Wikidata that similarly stores facts about the world
in data formats through which various apps can retrieve the data.
Researchers and journalists also use semantic technologies for search
engine optimization, fact-checking practices, and data sharing and
organization. This special issue thus focuses on such platformized versions
of fact production and examines the underlying infrastructures, histories,
and modeling techniques used in knowledge representation systems.
We are interested in quantitative, quali
