This will be starting in about 30 minutes.

On Mon, Dec 14, 2020 at 11:01 AM Janna Layton <[email protected]> wrote:

> Just a reminder that this Showcase will be happening on Wednesday.
>
> On Fri, Dec 11, 2020 at 11:22 AM Janna Layton <[email protected]>
> wrote:
>
>> Hello,
>>
>> The next Research Showcase will be live-streamed on Wednesday, December
>> 16, at 9:30 AM PST/17:30 UTC, and will be on the theme of disinformation
>> and reliability of sources in Wikipedia. In the first talk, Włodzimierz
>> Lewoniewski will present recent work around multilingual approaches for the
>> assessment of content quality and reliability of sources in Wikipedia
>> leveraging machine learning algorithms. In the second talk, Diego
>> Saez-Trumper will give an overview of ongoing work on fighting
>> disinformation in Wikipedia; specifically, the development of tools and
>> datasets aimed at supporting the discovery of suspicious content and
>> improving verifiability.
>>
>> Youtube stream: https://www.youtube.com/watch?v=v9Wcc-TeaEY
>>
>> As usual, you can join the conversation on IRC at #wikimedia-research.
>> You can also watch our past research showcases here:
>> https://www.mediawiki.org/wiki/Wikimedia_Research/Showcase
>>
>> Talk 1
>>
>> Speaker: Włodzimierz Lewoniewski (Poznań University of Economics and
>> Business, Poland)
>>
>> Title: Quality assessment of Wikipedia and its sources
>>
>> Abstract: Information in Wikipedia can be edited in over 300 languages
>> independently. Therefore often the same subject in Wikipedia can be
>> described differently depending on language edition. In order to compare
>> information between them one usually needs to understand each of considered
>> languages. We work on solutions that can help to automate this process.
>> They leverage machine learning and artificial intelligence algorithms. The
>> crucial component, however, is assessment of article quality therefore we
>> need to know how to define and extract different quality measures. This
>> presentation briefly introduces some of the recent activities of Department
>> of Information Systems at Poznań University of Economics and Business
>> related to quality assessment of multilingual content in Wikipedia. In
>> particular, we
>>
>> demonstrate some of the approaches for the reliability assessment of
>> sources in Wikipedia articles. Such solutions can help to enrich various
>> language editions of Wikipedia and other knowledge bases with information
>> of better quality.
>>
>>
>> Talk 2
>>
>> Speaker: Diego Saez-Trumper (Research, Wikimedia Foundation)
>>
>> Title: Challenges on fighting Disinformation in Wikipedia: Who has the
>> (ground-)truth?
>>
>> Abstract: Different from the major social media websites where the fight
>> against disinformation mainly refers to preventing users to massively
>> replicate fake content, fighting disinformation in Wikipedia requires tools
>> that allows editors to apply the content policies of: verifiability,
>> non-original research, and neutral point of view. Moreover, while other
>> platforms try to apply automatic fact checking techniques to verify
>> content, the ground-truth for such verification is done based on Wikipedia,
>> for obvious reasons we can't follow the same pipeline for fact checking
>> content on Wikipedia. In this talk we will explain the ML approach we are
>> developing to build tools to efficiently support wikipedians to discover
>> suspicious content and how we collaborate with external researchers on this
>> task. We will also describe a group of datasets we are preparing to share
>> with the research community in order to produce state-of-the-art algorithms
>> to improve the verifiability of content on Wikipedia.
>>
>> --
>> Janna Layton (she/her)
>> Administrative Associate - Product & Technology
>> Wikimedia Foundation <https://wikimediafoundation.org/>
>>
>
>
> --
> Janna Layton (she/her)
> Administrative Associate - Product & Technology
> Wikimedia Foundation <https://wikimediafoundation.org/>
>


-- 
Janna Layton (she/her)
Administrative Associate - Product & Technology
Wikimedia Foundation <https://wikimediafoundation.org/>
_______________________________________________
Analytics mailing list
[email protected]
https://lists.wikimedia.org/mailman/listinfo/analytics

Reply via email to