Hi all,

The next Research Showcase, with the theme of *Wikimedia and LGBTQIA+*,
will be live-streamed Wednesday, June 21 at 16:30 UTC. Find your local time
here <https://zonestamp.toolforge.org/1687365012>.

YouTube stream: https://www.youtube.com/watch?v=AOD2ZdxRNfo

You can join the conversation on IRC at #wikimedia-research or on the
YouTube chat.

This month's presentations:

   - *Multilingual Contextual Affective Analysis of LGBT People Portrayals
   in Wikipedia*
   - *Speaker*: Chan Park, Carnegie Mellon University
      - *Abstract*: In this talk, I present our research on analyzing the
      portrayal of LGBT individuals in their biographies on Wikipedia, with a
      particular focus on subtle word connotations and cross-cultural
      comparisons. We aim to address two primary research questions: 1) How can
      we effectively measure the nuanced connotations of words in multilingual
      texts, which reflect sentiments, power dynamics, and agency? 2)
How can we
      analyze the portrayal of a specific group, such as the LGBT
community, and
      compare these portrayals across different languages? To answer these
      questions, we collect the Multilingual Contextualized Connotation Frames
      dataset, comprising 2,700 examples in English, Spanish, and Russian. We
      also develop a new multilingual model based on pre-trained multilingual
      language models. Additionally, we devise a matching algorithm to
construct
      a comparison corpus for the target corpus, isolating the attribute of
      interest. Finally, we showcase how our developed models and constructed
      corpora enable us to conduct cross-cultural analysis of LGBT People
      Portrayals on Wikipedia. Our results reveal systematic differences in how
      the LGBT community is portrayed across languages, surfacing cultural
      differences in narratives and signs of social biases.
      - *Paperː* Park, C. Y., Yan, X., Field, A., & Tsvetkov, Y. (2021,
      May). Multilingual contextual affective analysis of LGBT people
portrayals
      in Wikipedia. In Proceedings of the International AAAI Conference on Web
      and Social Media (Vol. 15, pp. 479-490).
      <https://arxiv.org/pdf/2010.10820.pdf>


   - *Visual gender biases in Wikipediaː A systematic evaluation across the
   ten most spoken languages*
      - *Speaker*: Daniele Metilli, University College London
      - *Abstract*: Wikidata Gender Diversity (WiGeDi) is a one-year
      project funded through the Wikimedia Research Fund. The project
is studying
      gender diversity in Wikidata, focusing on marginalized gender identities
      such as those of trans and non-binary people, and adopting a queer and
      intersectional feminist perspective. The project is organised in three
      strands — model, data, and community. First, we are looking at how the
      current Wikidata ontology model represents gender, and the
extent to which
      this representation is inclusive of marginalized gender
identities. We are
      analysing the data stored in the knowledge base to gather insights and
      identify possible gaps and biases. Finally, we are looking at how the
      community has handled the move towards the inclusion of a wider
spectrum of
      gender identities by studying a corpus of user discussions through
      computational linguistics methods. This presentation will report on the
      current status of the Wikidata Gender Diversity project and the
envisioned
      outcomes. We will discuss the main challenges that we are facing and the
      opportunities that our project will potentially enable, on Wikidata and
      beyond.
      - *Paperː* Metilli D. & Paolini C. (in press). ‘Non-binary gender
      representation in Wikidata’. In: Provo A., Burlingame K. & Watson B.M.
      Ethics in Linked Data. Litwin Books. <https://wigedi.com/chapter.pdf>

You can watch our past Research Showcases here:
https://www.mediawiki.org/wiki/Wikimedia_Research/Showcase


Hope you can join us!

Warm regards,

-- 

*Pablo Aragón (he/him)*
Research Scientist
Wikimedia Foundation
https://research.wikimedia.org
_______________________________________________
Wikimedia-l mailing list -- wikimedia-l@lists.wikimedia.org, guidelines at: 
https://meta.wikimedia.org/wiki/Mailing_lists/Guidelines and 
https://meta.wikimedia.org/wiki/Wikimedia-l
Public archives at 
https://lists.wikimedia.org/hyperkitty/list/wikimedia-l@lists.wikimedia.org/message/YAZBRGWF3XKYLTXLCKJU4MKA6B4X7WZX/
To unsubscribe send an email to wikimedia-l-le...@lists.wikimedia.org

Reply via email to