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Big Data vs. Slow Understanding?

Abstract The paper looks into the practice of a computer-assisted discourse analysis. Centring on the decisions and procedures that go into reconstructing multimodal frames from transmedia discourse, the paper has two aims. For one, it discusses the chances and challenges automatic text analysis has to address in facing the vast amounts of multimodal discourse that emerge in convergent media. Building on that, the paper explains the methodological premises and methodical procedures of a discourse analysis employing the computer-assisted qualitative data analysis software Atlas.ti. As such, it presents an investigation that does not answer the current prevalence of available ‘big data’ with computer power but explores the interplay between an interpretative analysis and technological support. It does so by using material from the discourse on the so-called Handygate affair. There, state authorities collected mobile phone data during the commemorative events of the Dresden bombings in February 2011. They thus created a big data collection which became the subject of public attention and was either framed as illegal and extensive instrument of state surveillance or as an efficient and accurate tool for law enforcement and targeted prosecution.