| Zusammenfassung |
From pandemics and bank runs to gangnam style, we live in contagious times, where society is continually re-composed and even decomposed through its contacts, imitative relations and vibratory events - and these in turn can both generate and be responsive to large amounts of digital trace data. As a result, there's a conceptual and methodological challenge, to effectively re-tool social science, to hone its capacity for influencing behaviour and informing interventions, by strategically and intelligently mining new data resources in order to build an empirically rich and theoretically informed epidemiology of the social. What makes some things, viruses or affects, affective? What gives them a propensity to move, transform and infect? Can we reach some conclusions on transmissibility, its spatial and temporal variations? And what effects, if any, do different contagious domains have on our understanding of this social epidemiology? In the social sciences we haven't as yet capitalised on the possibilities of bringing these resources together to inform a critical approach to reality mining. To that end we contagion invloves an international and interdisciplinary team working collaboratively to explore 3 contagious phenomena, in order to refine methods, explore spatial analysis and theory, to compare contagious domains and identify avenues for further work and impact. The three phenomena are: food scares, influenza events and financial contagion. Each of these is associated with large data sets that not only help us to access transmission but are also part and parcel of the contagious phenomena themselves. So a food scare event is relayed on micro-blogging sites like twitter and achieves an affective valency that might other have been impossible. Moreover, this affective state can transform the contagious event, prompting network changes, behaviours and so on. This project will analyse these kinds of events and their social and spatial character, through geographically and time stamped 'twitter' data. Similarly, we can now explore the evolution of flu lineages through large data sets and link these to our understanding of changes in human/ animal interfaces. Finally, the project will explore the use of social media data use within in the commercial sector and in finance. The design and use of sentiment analysis to measure mood and in turn to adjust trading behaviour (either automated or otherwise) provides a fascinating case of the use of big data to influence behaviour and perform network effects. The project will use these disparate contagious domains to investigate the degree to which contagion is conceptually suited to describing such a seemingly wide ranging if potentially over-lapping set of phenomena. |
