Analyzing Media Messages: Using Quantitative Content by Daniel Riffe
By Daniel Riffe
Analyzing Media Messages is a primer for studying the means of systematic, quantitative research of verbal exchange content material. wealthy with examples of contemporary and vintage purposes, it presents ideas to difficulties encountered in engaging in content material research, and it really is written in order that scholars can easily comprehend and observe the techniques.
This completely revised 3rd variation contains present and interesting examples for ultra-modern scholars, as well as a few traditionally vital circumstances. It emphasizes verbal exchange of visible imagery and reviews of ads content material. assets at the book’s significant other site offer extra fabrics for college students and teachers, together with present protocols, net hyperlinks, and a bibliography of content material research equipment articles.
This quantity is meant to be used as a first-rate textual content for content material research coursework, or as a supplemental textual content in learn equipment classes. it's also an vital reference for researchers in mass media fields, political technology, and different social and behavioral sciences.
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Extra resources for Analyzing Media Messages: Using Quantitative Content Analysis in Research
As Kerlinger (1973) stated, content analysis “can be applied to available materials and to materials especially produced for particular research problems” (p. 527). For example, existing “current” online content or archived content, whether from newspapers, magazines, video, blog posts, tweets, and so on, may be analyzed, or participants may be placed in experimental situations or conditions, and the content they Defining Content Analysis as a Social Science Tool 23 then produce may be subjected to scrutiny as in the framing and “thought-listing” experiments (de Vreese, 2004, 2010) described in chapter 1 (this volume).
Moreover, the hypotheses formulated to build on or extend such research give guidance on how to measure the variables to be explored. So an explicit hypothesis (or question) guides both data collection and variable measurement in good research design. A hypothesis explicitly asserts that a state or level of one variable is associated with a state or level in another variable. A hypothesis may assert an actual causal relationship or merely a predictable association (discussed later). Which of these two assumptions is made will guide research design.
If early work in new content areas or new technologies is often necessarily descriptive, consider unprecedented events like the September 11, 2001, terrorist attacks, the Oklahoma City bombing, hurricane Katrina, or the April 2010 BP spill. Such events are so far from the routine of daily journalism that the response of news workers and organizations warrants description (Reynolds & Barnett, 2003). Some descriptive data are involved in the second goal of content analysis specified in the definition: to draw inferences about meaning or infer from the communication to its context, both of production and consumption.