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2. Social-IQ: A Question Answering Benchmark for Artificial Social Intelligence

   Zadeh, Amir; Chan, Michael; Liang, Paul Pu; Tong, Edmund; Morency, Louis-Philippe (January 2019, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR))

   As intelligent systems increasingly blend into our everyday life, artificial social intelligence becomes a prominent area of research. Intelligent systems must be socially intelligent in order to comprehend human intents and maintain a rich level of interaction with humans. Human language offers a unique unconstrained approach to probe through questions and reason through answers about social situations. This unconstrained approach extends previous attempts to model social intelligence through numeric supervision (e.g. sentiment and emotions labels). In this paper, we introduce the Social-IQ, an unconstrained benchmark specifically designed to train and evaluate socially intelligent technologies. By providing a rich source of open-ended questions and answers, Social-IQ opens the door to explainable social intelligence. The dataset contains rigorously annotated and validated videos, questions and answers, as well as annotations for the complexity level of each question and answer. Social- IQ contains 1, 250 natural in-thewild social situations, 7, 500 questions and 52, 500 correct and incorrect answers. Although humans can reason about social situations with very high accuracy (95.08%), existing state-of-the-art computational models struggle on this task. As a result, Social-IQ brings novel challenges that will spark future research in social intelligence modeling, visual reasoning, and multimodal question answering (QA). 

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3. Who Puts the "Social" in "Social Computing"?: Using A Neurodiversity Framing to Review Social Computing Research

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   Baillargeon, Philip; Yoon, Jina; Zhang, Amy (May 2025, Proceedings of the ACM on Human-Computer Interaction)

   Human-Computer Interaction (HCI) and Computer Supported Collaborative Work (CSCW) have a longstanding tradition of interrogating the values that underlie systems in order to create novel and accessible experiences. In this work, we use a neurodiversity framing to examine how people with ways of thinking, speaking, and being that differ from normative assumptions are perceived by researchers seeking to study and design social computing systems for neurodivergent people. From a critical analysis of 84 publications systematically gathered across a decade of social computing research, we determine that research into social computing with neurodiverse participants is largely medicalized, adheres to historical stereotypes of neurodivergent children and their families, and is insensitive to the wide spectrum of neurodivergent people that are potential users of social technologies. When social computing systems designed for neurodivergent people rely upon a conception of disability that restricts expression for the sake of preserving existing norms surrounding social experience, the result is often simplistic and restrictive systems that prevent users from being social in a way that feels natural and enjoyable. We argue that a neurodiversity perspective informed by critical disability theory allows us to engage with alternative forms of sociality as meaningful and desirable rather than a deficit to be compensated for. We conclude by identifying opportunities for researchers to collaborate with neurodivergent users and their communities, including the creation of spectrum-conscious social systems and the embedding of double empathy into systems for more equitable design. 

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4. A split sex ratio in solitary and social nests of a facultatively social bee

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5. A neurodevelopmental disorders perspective into music, social attention, and social bonding

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   Kasdan, Anna; Gordon, Reyna L.; Lense, Miriam D. (January 2021, Behavioral and Brain Sciences)

   null (Ed.)

   Abstract Our commentary addresses how two neurodevelopmental disorders, Williams syndrome and autism spectrum disorder, provide novel insights into the credible signaling and music and social bonding hypotheses presented in the two target articles. We suggest that these neurodevelopmental disorders, characterized by atypical social communication, allow us to test hypotheses about music, social bonding, and their underlying neurobiology. 

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