Have We Even Solved the First ‘Big Data Challenge?’ Practical Issues Concerning Data Collection and Visual Representation for Social Media ... View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2016

AUTHORS

Phillip Brooker , Julie Barnett , Timothy Cribbin , Sanjay Sharma

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. More... »

PAGES

34-50

Book

TITLE

Digital Methods for Social Science

ISBN

978-1-349-55862-9
978-1-137-45366-2

Identifiers

URI

http://scigraph.springernature.com/pub.10.1057/9781137453662_3

DOI

http://dx.doi.org/10.1057/9781137453662_3

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1021270037


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