Analyzing Blending Social and Mass Media Audiences Through the Lens of Computer-Mediated Discourse

Analyzing Blending Social and Mass Media Audiences Through the Lens of Computer-Mediated Discourse

Asta Zelenkauskaite
Copyright: © 2018 |Pages: 25
ISBN13: 9781522556374|ISBN10: 1522556370|EISBN13: 9781522556381
DOI: 10.4018/978-1-5225-5637-4.ch050
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MLA

Zelenkauskaite, Asta. "Analyzing Blending Social and Mass Media Audiences Through the Lens of Computer-Mediated Discourse." Social Media Marketing: Breakthroughs in Research and Practice, edited by Information Resources Management Association, IGI Global, 2018, pp. 1022-1046. https://doi.org/10.4018/978-1-5225-5637-4.ch050

APA

Zelenkauskaite, A. (2018). Analyzing Blending Social and Mass Media Audiences Through the Lens of Computer-Mediated Discourse. In I. Management Association (Ed.), Social Media Marketing: Breakthroughs in Research and Practice (pp. 1022-1046). IGI Global. https://doi.org/10.4018/978-1-5225-5637-4.ch050

Chicago

Zelenkauskaite, Asta. "Analyzing Blending Social and Mass Media Audiences Through the Lens of Computer-Mediated Discourse." In Social Media Marketing: Breakthroughs in Research and Practice, edited by Information Resources Management Association, 1022-1046. Hershey, PA: IGI Global, 2018. https://doi.org/10.4018/978-1-5225-5637-4.ch050

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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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