Studying images in social media poses specific methodological challenges, which in turn have directed scholarly attention toward the computational interpretation of visual data. When analyzing large numbers of images, both traditional content analysis as well as cultural analytics have proven valuable. However, these techniques do not take into account the contextualization of images within a socio-technical environment. As the meaning of social media images is co-created by online publics, bound through networked practices, these visuals should be analyzed on the level of their networked contextualization. Although machine vision is increasingly adept at recognizing faces and features, its performance in grasping the meaning of social media images remains limited. Combining automated analyses of images with platform data opens up the possibility to study images in the context of their resonance within and across online discursive spaces. This article explores the capacities of hashtags and retweet counts to complement the automated assessment of social media images, doing justice to both the visual elements of an image and the contextual elements encoded through the hashtag practices of networked publics.
Post-partum hemorrhaging is a medical emergency that occurs during childbirth and, in extreme cases, can be life-threatening. It is the number one cause of maternal mortality worldwide. High-quality training of medical staff can contribute to early diagnosis and work towards preventing escalation towards more serious cases. Healthcare education uses manikin-based simulators to train obstetricians for various childbirth scenarios before training on real patients. However, these medical simulators lack certain key features portraying important symptoms and are incapable of communicating with the trainees. The authors present a digital embodiment agent that can improve the current state of the art by providing a specification of the requirements as well as an extensive design and development approach. This digital embodiment allows educators to respond and role-play as the patient in real time and can easily be integrated with existing training procedures. This research was performed in collaboration with medical experts, making a new contribution to medical training by bringing digital humans and the representation of affective interfaces to the field of healthcare.
Lives of Data maps the historical and emergent dynamics of big data, computing, and society in India. Data infrastructures are now more global than ever before. In much of the world, new sociotechnical possibilities of big data and artificial intelligence are unfolding under the long shadows cast by infra/structural inequalities, colonialism, modernization, and national sovereignty. This book offers critical vantage points for looking at big data and its shadows, as they play out in uneven encounters of machinic and cultural relationalities of data in India’s socio-politically disparate and diverse contexts.Lives of Data emerged from research projects and workshops at the Sarai programme, Centre for the Study of Developing Societies. It brings together fifteen interdisciplinary scholars and practitioners to set up a collaborative research agenda on computational cultures. The essays offer wide-ranging analyses of media and techno-scientific trajectories of data analytics, disruptive formations of digital economy, and the grounded practices of data-driven governance in India. Encompassing history, anthropology, science and technology studies (STS), media studies, civic technology, data science, digital humanities, and journalism, the essays open up possibilities for a truly situated global and sociotechnically specific understanding of the many lives of data.
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