Hi everyone,
The next Research Showcase will be live-streamed tomorrow Wednesday,
April 17, at 9:30 AM PST / 16:30 UTC. Find your local time here. The
theme for this showcase is Supporting Multimedia on Wikipedia.
You are welcome to watch via the YouTube stream:
https://www.youtube.com/watch?v=wpSQD9Bc8Ek. As usual, you can join
the conversation in the YouTube chat as soon as the showcase goes
live.
This month's presentations:
Towards image accessibility solutions grounded in communicative principles
By Elisa Kreiss
Images have become an omnipresent communicative tool -- and this is no
exception on Wikipedia. However, the undeniable benefits they carry
for sighted communicators turns into a serious accessibility challenge
for people who are blind or have low vision (BLV). BLV users often
have to rely on textual descriptions of those images to equally
participate in an ever-increasing image-dominated online lifestyle. In
this talk, I will present how framing accessibility as a communication
problem highlights important ways forward in redefining image
accessibility on Wikipedia. I will present the Wikipedia-based dataset
Concadia and use it to discuss the successes and shortcomings of image
captions and alt texts for accessibility, and how the usefulness of
accessibility descriptions is fundamentally contextual. I will
conclude by highlighting the potential and risks of AI-based solutions
and discussing implications for different Wikipedia editing
communities.
Automatic Multi-Path Web Story Creation from a Structural Article
By Daniel Nkemelu
Web articles such as Wikipedia serve as one of the major sources of
knowledge dissemination and online learning. However, their in-depth
information--often in a dense text format--may not be suitable for
mobile browsing, even in a responsive user interface. We propose an
automatic approach that converts a structured article of any length
into a set of interactive Web Stories that are ideal for mobile
experiences. We focused on Wikipedia articles and developed
Wiki2Story, a pipeline based on language and layout models, to
demonstrate the concept. Wiki2Story dynamically slices an article and
plans one to multiple Story paths according to the document hierarchy.
For each slice, it generates a multi-page summary Story composed of
text and image pairs in visually appealing layouts. We derived design
principles from an analysis of manually created Story practices. We
executed our pipeline on 500 Wikipedia documents and conducted user
studies to review selected outputs. Results showed that Wiki2Story
effectively captured and presented salient content from the original
articles and sparked interest in viewers.
--
Kinneret Gordon
Lead Research Community Officer
Wikimedia Foundation