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pro vyhledávání: '"Yoder, Michael Miller"'
Online multiplayer games like League of Legends, Counter Strike, and Skribbl.io create experiences through community interactions. Providing players with the ability to interact with each other through multiple modes also opens a Pandora box. Toxic b
Externí odkaz:
http://arxiv.org/abs/2407.04383
Autor:
Yoder, Michael Miller, Perry, Chloe, Brown, David West, Carley, Kathleen M., Pruden, Meredith L.
Online communities of involuntary celibates (incels) are a prominent source of misogynist hate speech. In this paper, we use quantitative text and network analysis approaches to examine how identity groups are discussed on incels-dot-is, the largest
Externí odkaz:
http://arxiv.org/abs/2306.15745
We present a dataset and classifier for detecting the language of white supremacist extremism, a growing issue in online hate speech. Our weakly supervised classifier is trained on large datasets of text from explicitly white supremacist domains pair
Externí odkaz:
http://arxiv.org/abs/2306.15732
Autor:
Madani, Navid, Bandyopadhyay, Rabiraj, Swire-Thompson, Briony, Yoder, Michael Miller, Joseph, Kenneth
Social media platforms provide users with a profile description field, commonly known as a ``bio," where they can present themselves to the world. A growing literature shows that text in these bios can improve our understanding of online self-present
Externí odkaz:
http://arxiv.org/abs/2305.09548
Autor:
Diab, Ahmad, Jagdagdorj, Bolor-Erdene, Ng, Lynnette Hui Xian, Lin, Yu-Ru, Yoder, Michael Miller
White supremacist extremist groups are a significant domestic terror threat in many Western nations. These groups harness the Internet to spread their ideology via online platforms: blogs, chat rooms, forums, and social media, which can inspire viole
Externí odkaz:
http://arxiv.org/abs/2303.07838
This paper investigates how hate speech varies in systematic ways according to the identities it targets. Across multiple hate speech datasets annotated for targeted identities, we find that classifiers trained on hate speech targeting specific ident
Externí odkaz:
http://arxiv.org/abs/2210.10839
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Stereotypes inform how we present ourselves and others, and in turn how we behave. They are thus important to measure. Recent work has used projections of embeddings from Distributional Semantic Models (DSMs), such as BERT, to perform these measureme
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1eb8d186f330f67a2703f06b65b5308c
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Akademický článek
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