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.

Message Units and Sampling

This chapter introduces the initial methodological decisions necessary in content analytic research. Various types of units are considered, showing the range of choices in selecting the unit or units for a given study. There is discussion of proper probability sampling techniques, including simple random sampling, systematic sampling, cluster sampling, stratified sampling, and multistage sampling. Issues of access to sampling frames and message archive options are explored.


In content analysis, a unit is an identifiable message or message component that (a) serves as the basis for identifying the population and drawing a sample, (b) is the component on which variables are measured, and/or (c) serves as the basis for reporting analyses. Units can be words, characters, themes, time periods, statements or turns ...

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