Hi everyone,
This month's showcase focused on *supporting multimedia on Wikipedia* will
start in about 45 minutes. Please join us at
https://www.youtube.com/watch?v=wpSQD9Bc8Ek.
On Tue, Apr 16, 2024 at 8:25?AM Kinneret Gordon <kgordon@wikimedia.org>
wrote:
> 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
>
This month's showcase focused on *supporting multimedia on Wikipedia* will
start in about 45 minutes. Please join us at
https://www.youtube.com/watch?v=wpSQD9Bc8Ek.
On Tue, Apr 16, 2024 at 8:25?AM Kinneret Gordon <kgordon@wikimedia.org>
wrote:
> 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
>