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Analyzing Blending Social and Mass Media Audiences through the Lens of Computer-Mediated Discourse
Abstract
In recent years, mass media content has undergone a blending process with social media. Large amounts of text-based social media content have not only shaped mass media products, but also provided new opportunities to access audience behaviors through these large-scale datasets. Yet, evaluating a plethora of audience contents strikes one as methodologically challenging endeavor. This study illustrates advantages and applications of a mixed-method approach that includes quantitative computer-mediated discourse analysis (CMDA) and automated analysis of content frequency. To evaluate these methodologies, audience comments consisting of Facebook comments and SMS mobile texting to Italian radio-TV station RTL 102.5 were analyzed. Blended media contents through computer-mediated discourse analysis expand horizons for theoretical and methodological audience analysis research in parallel to established audience analysis metrics.
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