Hi all, A friendly reminder that this is starting in about 30 minutes. We hope you can join us!
Best, On Thu, Jun 15, 2023 at 10:53 AM Pablo Aragón <para...@wikimedia.org> wrote: > Hi again, > > There was an error in the previous message: the title of the second > presentation is *“How do you represent my gender? Challenges and > opportunities from the Wikidata Gender Diversity project”*. > > Hope you can join us! > > Warm regards, > > On Thu, Jun 15, 2023 at 9:16 AM Pablo Aragón <para...@wikimedia.org> > wrote: > >> 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 >> >
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