This digest provides an introduction to content analysis, a systematic, replicable technique for compressing many words of a text into fewer content categories based on explicit rules of coding. This allows inferences to be made that can then be corroborated using other methods of data collection. In a technical sense, content analysis is not restricted to the domain of text, but in order to allow for replication, the technique can only be applied to data that are durable in nature. Content analysis can be a powerful tool for determining authorship, and it is useful for examining trends and patterns in documents. Content analysis also can provide an empirical basis for monitoring shifts in public opinion. K. Krippendorff has identified six questions regarding content analysis that must be addressed to clarify the data being analyzed and the target of the inferences to be drawn. Content analysis is more than a word-frequency count, although such counts may be a useful starting point. Content analysis is particularly rich because of its reliance on coding and categorizing data. Ways of defining coding units are discussed. There are also issues of reliability and validity that must be addressed in content analysis, but when used properly, it is a powerful data reduction technique. (SLD)