This data represents two long-term searches for Twitter data for two hashtags: #badgercull and #tbfree that correspond to the public controversy around the cull of badgers in the UK in the Autumn of 2013. We live in contagious times, where society is continually re-made and even unmade through its contacts - and these in turn can both generate and be responsive to large amounts of digital trace data. As a result, this research addresses conceptual and methodological challenges 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 contagion involves an international and interdisciplinary team working collaboratively to explore three contagious phenomena (influenza, food scares and finance), in order to refine methods, explore spatial analysis and theory, to compare contagious domains and identify avenues for further work and impact.

The data provided are the output of searches for two hashtags #badgercull and #tbfree using the platform 'ScraperWiki', which acted as WYSIWYG interface to the Twitter search API.