Content analysis is one of the most important but complex research methodologies in the social sciences. In this thoroughly updated Second Edition of The Content Analysis Guidebook, author Kimberly Neuendorf draws on examples from across numerous disciplines to clarify the complicated aspects of content analysis through step-by-step instruction and practical advice. Throughout the book, the author also describes a wide range of innovative content analysis projects from both academia and commercial research that provide readers with a deeper understanding of the research process and its many real-world applications.

Variables and Predictions
Variables and Predictions

Scholarly work generally proceeds from theory, with research questions, hypotheses, or both derived directly from the theory. This is the ideal, an application of the hypothetico-deductive model of science. In this model, hypotheses and research questions will flow from theory, and the variables that need to be measured will be apparent in these predictions and questions. A discussion of formats for hypotheses and research questions is provided later in this chapter. In actuality, a review of the content analysis literature indicates that many content analyses do not test formal hypotheses or research questions, and those that do often do not provide a real test of theory. In an overview of studies reviewing published content analyses, Manganello and Fishbein concluded ...

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