Abstract

Thanks to an influx of data collection and analytic software, harvesting and visualizing ‘big’ social media data1 is becoming increasingly feasible as a method for social science researchers. Yet while there is an emerging body of work utilizing social media as a data resource, there are a number of computational issues affecting data collection. These issues may problematize any conclusions we draw from our research work, yet for the large part, they remain hidden from the researcher’s view. We contribute towards the burgeoning literature which critically addresses various fundamental concerns with big data (see boyd and Crawford, 2012; Murthy, 2013; Rogers, 2013). However, rather than focusing on epistemological, political or theoretical issues — these areas are very ably accounted for by the authors listed above, and others — we engage with a different concern: how technical aspects of computational tools for capturing and handling social media data may impact our readings of it. This chapter outlines and explores two such technical issues as they occur for data taken from Twitter.

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