Social media continues to grow in its scope, importance, and toxicity. Hate speech is ever-present in today’s social media, and causes or contributes to dangerous situations in the real world for those it targets. Anti-Muslim bias and hatred has escalated in both public life and social media in recent years. This talk will overview a new and ongoing project in identifying Islamophobia in social media using techniques from Natural Language Processing. I will describe our methods of data collection and annotation, and discuss some of the challenges we have encountered thus far. In addition I’ll describe some of the pitfalls that exist for any effort attempting to identify hate speech (automatically or not).

In this short talk I use the conceptual framing of a digital enclosure to consider the way Uyghur and Kazakh societies in Northwest China have been enveloped by a surveillance system over the past decade. I show how novel enclosures are produced and, in turn, construct new frontiers in capital accumulation and state power. The Turkic Muslim digital enclosure system began with the construction of 3-G cellular wireless networks which provided Uyghurs and Kazakhs with interactive smart-phone enabled capabilities across time and space. But over time state authorities paid private technology companies to build a data-intensive system with a wide range of spatial scales and information analytics that came to center on "Muslim" social media assessment and ethno-racialized face recognition technology. This complex matrix of overlaid enclosures assessed and controlled the movements and behavior of Muslims in increasingly intimate ways, resulting in mass detentions in "reeducation" camps. What makes the case in Northwest China unique beyond its scale and cruelty, is that in this context rather than banishing targeted populations solely to human warehousing spaces such as peripheral ghettos, camps or prisons, the digital enclosure works to explicitly “reeducate” the population as industrial workers and implement a forced labor regime.

In an era unstructured data abundance, you would think that we have solved our data requirements for building robust systems for language processing. However, this is not the case if we think on a global scale with over 7000 languages where only a handful have digital resources. Moreover, systems at scale with good performance typically require annotated resources.The existence of a handful of resources in a some languages is a reflection of the digital disparity in various societies leading to inadvertent biases in systems. In this talk I will show some solutions for low resource scenarios, both cross domain and genres as well as cross lingually.

In this short talk, Roya Pakzad will speak about her current project entitled "Nuanced Counter-Narratives of Being Muslim Online." The goal of this project is to gain a deeper understanding of how marginalized groups create counter-narratives, who amplifies them, how sustainable they are, and how their impact differs. By providing various examples, she will also touch on how technology companies' business models and their third-party relationships impact Muslims and people from Muslim-majority countries. The talk will conclude with recommendations for design and policy interventions.

The workshop will conclude with a discussion with authors and organizers.