This investigation explores relations between 1) a theory of human cognition, called Embodied Cognition, 2) the design of interactive systems and 3) the practice of ‘creative group meetings’ (of which the so-called ‘brainstorm’ is perhaps the best-known example). The investigation is one of Research-through-Design (Overbeeke et al., 2006). This means that, together with students and external stakeholders, I designed two interactive prototypes. Both systems contain a ‘mix’ of both physical and digital forms. Both are designed to be tools in creative meeting sessions, or brainstorms. The tools are meant to form a natural, element in the physical meeting space. The function of these devices is to support the formation of shared insight: that is, the tools should support the process by which participants together, during the activity, get a better grip on the design challenge that they are faced with. Over a series of iterations I reflected on the design process and outcome, and investigated how users interacted with the prototypes.
Studying images in social media poses specific methodological challenges, which in turn have directed scholarly attention towards 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 circulation and contextualization of images within a socio-technical environment. As the meaning of social media images is co-created by networked 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 is limited. However, combining automated analyses of images - broken down by their compositional elements - with repurposing platform data opens up the possibility to study images in the context of their resonance within and across online discursive spaces. This paper explores the capacities of platform data - hashtag modularity 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 by networked publics that co-create meaning.
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