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Modern social media platforms like Twitch, YouTube, etc., embody an open space for content creation and consumption. However, an unintended consequence of such content democratization is the proliferation of toxicity and abuse that content creators get subjected to. Commercial and volunteer content moderators play an indispensable role in identifying bad actors and minimizing the scale and degree of harmful content. Moderation tasks are often laborious, complex, and even if semi-automated, they involve high-consequence human decisions that affect the safety and popular perception of the platforms. In this paper, through an interdisciplinary collaboration among researchers from social science, human-computer interaction, and visualization, we present a systematic understanding of how visual analytics can help in human-in-the-loop content moderation. We contribute a characterization of the data-driven problems and needs for proactive moderation and present a mapping between the needs and visual analytic tasks through a task abstraction framework. We discuss how the task abstraction framework can be used for transparent moderation, design interventions for moderators’ well-being, and ultimately, for creating futuristic human-machine interfaces for data-driven content moderation. 

The cognitive abilities of humans are distinctive among primates, but their molecular and cellular substrates are poorly understood. We used comparative single-nucleus transcriptomics to analyze samples of the middle temporal gyrus (MTG) from adult humans, chimpanzees, gorillas, rhesus macaques, and common marmosets to understand human-specific features of the neocortex. Human, chimpanzee, and gorilla MTG showed highly similar cell-type composition and laminar organization as well as a large shift in proportions of deep-layer intratelencephalic-projecting neurons compared with macaque and marmoset MTG. Microglia, astrocytes, and oligodendrocytes had more-divergent expression across species compared with neurons or oligodendrocyte precursor cells, and neuronal expression diverged more rapidly on the human lineage. Only a few hundred genes showed human-specific patterning, suggesting that relatively few cellular and molecular changes distinctively define adult human cortical structure.