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Content Analysis
Content analysis is a research technique for making replicable and valid inferences from texts (or other meaningful matter) to the context of their use.
This entry further explores the definition and conceptions of content analysis. It then provides information on its conceptual framework and the steps involved in performing content analysis.
Definition and Conception
The phrase content analysis, first mentioned in a 1941 paper by Douglas Waples and Bernard Berelson, became defined in 1948 by Paul F. Lazarsfeld and Berelson. Webster's Dictionary has listed content analysis since its 1961 edition. However, the practice of analyzing media matter is almost as old as writing. It became of interest to the church, worried about the effects of the written word other than God's; to governments, trying to settle political, legal, and religious disputes; to journalists, hoping to document the changes in newspaper publishing due to its commercialization and popularization; to corporations interested in surveying their symbolic environments for opportunities and threats; and to social scientists, originally drawn into the competition between the press and newly emerging media, then radio and television, but soon discovering the importance of all kinds of mediated communication to understand social, political, economic, and psychological phenomena. Communication research advanced content analysis, but owing to the proliferation of media and the recognition that humans define themselves and each other in communication, coordinate their beliefs and actions in communication, and construct the realities they live with in communication, content analysis is now used by literally all social sciences.
As a technique, content analysis embraces specialized procedures. It is teachable. Its use can be divorced from the authority of the researcher. As a research technique, content analysis can provide new kinds of understanding social phenomena or inform decisions on pertinent actions. Content analysis is a scientific tool.
All techniques are expected to be reliable. Scientific research techniques should result in replicable findings. Replicability requires research procedures to be explicit and communicable so that researchers, working at different times and perhaps under different circumstances, can apply them and come to the same conclusions about the same phenomena.
Scientific research must also yield valid results. To establish validity, research results must survive in the face of independently available evidence of what they claim. The methodological requirements of reliability and validity are not unique to content analysis but make particular demands on the technique that are not found as problematic in other methods of inquiry.
The reference to text is not intended to restrict content analysis to written material. The parenthetical phrase “or other meaningful matter” is to imply content analysis's applicability to anything humanly significant: images, works of art, maps, signs, symbols, postage stamps, songs, and music, whether mass produced, created in conversations, or private. Texts, whether composed by individual authors or produced by social institutions, are always intended to point their users to something beyond their physicality. However, content analysis does not presume that readers read a text as intended by its source; in fact, authors may be quite irrelevant, often unknown. In content analysis, available texts are analyzed to answer research questions not necessarily shared by everyone.
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- Descriptive Statistics
- Distributions
- Graphical Displays of Data
- Hypothesis Testing
- Alternative Hypotheses
- Beta
- Critical Value
- Decision Rule
- Hypothesis
- Nondirectional Hypotheses
- Nonsignificance
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- One-Tailed Test
- p Value
- Power
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- Significance Level, Interpretation and Construction
- Significance, Statistical
- Two-Tailed Test
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- “Coefficient Alpha and the Internal Structure of Tests”
- “Convergent and Discriminant Validation by the Multitrait-Multimethod Matrix”
- “Meta-Analysis of Psychotherapy Outcome Studies”
- “On the Theory of Scales of Measurement”
- “Probable Error of a Mean, The”
- “Psychometric Experiments”
- “Sequential Tests of Statistical Hypotheses”
- “Technique for the Measurement of Attitudes, A”
- “Validity”
- Aptitudes and Instructional Methods
- Doctrine of Chances, The
- Logic of Scientific Discovery, The
- Nonparametric Statistics for the Behavioral Sciences
- Probabilistic Models for Some Intelligence and Attainment Tests
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- Coefficient of Concordance
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- Classical Test Theory
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- Occam's Razor
- Paradigm
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- Probability, Laws of
- Theory
- Theory of Attitude Measurement
- Weber-Fechner Law
- Types of Variables
- Validity of Scores
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