Digital Mixed Content Analysis on Digital Platform Social Data: The Revival of a Research Technique and Its Declination Between Mixed and Digital Methods

Digital Mixed Content Analysis on Digital Platform Social Data: The Revival of a Research Technique and Its Declination Between Mixed and Digital Methods

DOI: 10.4018/978-1-7998-8473-6.ch021
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Abstract

The explosion of platform social data as digital secondary data, collectible through sophisticated and automatized query systems or algorithms, makes it possible to accumulate huge amounts of dense and miscellaneous data. The challenge for social researchers becomes how to extract meaning and not only trends in a quantitative as well as in a qualitative manner. Through the application of a digital mixed content analysis perspective to data analysis, in this contribution, the author will present the potentiality of a hybrid digitalized approach to social content. This perspective should be seen as an applied example of organizing a framework to guide the application of integrated methods of content analysis (quantitative and qualitative) but also integrated objects of analysis (individuals, relationships, and digital actions) on digital platform social data and to address their varied nature.
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Defining The Digital Mixed Content Analysis Approach

With respect to the possibilities introduced by the digital mixed content analysis approach, it would be fair to start by saying that something bigger is going on. In the years leading up to the digital turn (Lupton, 2014; Marres, 2017), viewed as a paradigm shift in social sciences, a new approach has been increasingly retrieved: The technique of content analysis is used to extract secondary meaning from information that allows researchers to recover and examine the nuances of behaviors, perceptions, and trends, from existing content produced with different purpose compared to those of research (Schreier, 2012; Krippendorff, 2018).

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