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Journalists, fact-checkers, academics, and community media are overwhelmed in their attempts to support communities suffering from gender-, race- and ethnicity-targeted information ecosystem threats, including but not limited to misinformation, hate speech, weaponized controversy and online-to-offline harassment. Yet, for a plethora of reasons, minoritized groups are underserved by current approaches to combat such threats. In this panel, we will present and discuss the challenges and open problems facing such communities and the researchers hoping to serve them. We will also discuss the current state-of-the-art as well as the most promising future directions, both within IR specifically, across Computer Science more broadly, as well as that requiring transdisciplinary and cross-sectoral collaborations. The panel will attract both IR practitioners and researchers and include at least one panelist outside of IR, with unique expertise in this space. 

Metadata on the times at which text and image messages were submitted to a tipline and public groups along with similarity/clustering data grouping messages. Please see the README file and the published paper for further details. Please cite the following publication if you use this data: Kazemi, A., Garimella, K., Shahi, G. K., Gaffney, D., & Hale, S. A. (2022). Research note: Tiplines to uncover misinformation on encrypted platforms: A case study of the 2019 Indian general election on WhatsApp. Harvard Kennedy School (HKS) Misinformation Review. https://doi.org/10.37016/mr-2020-91