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.

Results and Reporting
Results and Reporting

This chapter presents options for the reporting of content analysis findings. For certain analyses, timelines will be appropriate. Relationships among variables may be examined, and as long as good measurement and representative sampling from a known population of messages have been achieved, inferential statistics may be used. Relationships between content analysis variables and noncontent analysis (i.e., extramessage) variables may be explored via integrative data linking, as described in Chapter 2. However, it should be understood from the outset that it is beyond the scope of this book to provide the full breadth of information of a statistics textbook. Rather, this chapter is intended to educate the reader about the range of options for analyses and reportage, as well as ...

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