Data, the raw material from which information is derived, is stored, copied, moved and modified more easily than ever. This quantum leap reaches levels outside our imagination. Surrounded by sensors, recommendation systems, invisible algorithms, spreadsheets and blockchains, the ‘difference that makes a difference’ can no longer be identified. Big Data is a More Data ideology, driven by old school hypergrowth premisses. As Nathan Jurgenson once observed: “Big Data always stands in the shadow of the bigger data to come. The assumption is that there is more data today and there will necessarily be even more tomorrow, an expansion that will bring us ever closer to the inevitable pure ‘data totality.” (2) Nothing symbolizes the current hypergrowth obsession better than Big Data. Let’s investigate what happens when we apply degrowth to data and reserve datafication–as a decolonial project, a collective act of refusal, an ultimate sign of boredom. We’re done with you, data system, stand out of my light.
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Studying images on social media introduces several challenges that relate to the size of datasets and the different meaning-making grammars of social visuality; or as aptly pointed out by others in the field, it means ‘studying the qualitative on a quantitative scale’. Although cultural analytics provides an automated process through which patterns can be detected in large numbers of images, this methodology doesn’t account for other modalities of the image than the image itself. However, images circulating social media can (and should) be analyzed on the level of their audience as the latter is co-creating the meaning of images. Bridging the study of platform affordances and affect theory, this paper presents a novel methodology that repurposes Facebook Reactions to infer collective attitudes and performative emotional expressions vis á vis images shared on the large Syrian Revolution Network public page (+2M). We found visual patterns that co-occur with certain collective combinations of buttons, displaying how socio-technical features shape the discursive frameworks of online publics.
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