12:45:00 - 13:45:00,
Thursday 28 May, 2015
Gender detection algorithms, when used for media activism, have what I call ideological affordances — the kinds of feminism that these systems are more easily capable to support. Over the past three years, I have applied techniques for large-scale analysis of gender in the news, social media, and participatory media to collaborate with activists on interventions towards gender diversity online, on projects including UK news, journalistic sourcing, participatory media, speaker events, peer production, and online harassment, In this talk, I will discuss automatic detection of gender binaries and LGBTQ identities, new opportunities for collective action they afford, and the social behaviour and privacy issues raised by the kinds of feminism most easily supported by automated and semi-automated interventions.
Data Dump to delete
- Name: Nathan Matias
- Affiliation: MIT Media Lab Center for Civic Media
- Bio: Nathan Matias is a Ph.D. Student at the MIT Media Lab Center for Civic Media, a fellow at the Berkman Center for Internet and Society, and a DERP Institute fellow. Nathan researches technology for civic cooperation, activism, and expression through qualitative action research with communities, data analysis, software design, and field experiments. Most recently, Nathan has been conducting large-scale studies and interventions on the effects of gender bias, online harassment, gratitude, and peer thanks in social media, corporations, and creative communities like Wikipedia. Winner of the ACM’s Nelson Prize, Nathan has published data journalism, technology criticism, and literary writing for the Atlantic, the Guardian, and PBS. Before MIT, he worked at technology startups Texperts and SwiftKey, whose products have reached over a hundred million people worldwide. Nathan will be a PhD Intern at the Microsoft Research Social Media Collective in the summer of 2015.