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Content AnalysisContent analysis (also called: "textual analysis") is a standard methodology in the social sciences on the subject of communication content and can be applied in quantitative and qualitative ways. Harold Lasswell formulated the core questions of content analysis: "Who says what, to whom, why, to what extend and with what effect?". Ole Holsti (1969) offers a broad definition of content analysis as "any technique for making inferences by objectively and systematically identifying specified characteristics of messages" (p. 14). The method of content analysis enables the researcher to include large amounts of textual information and identify systematically its properties, e.g. the frequencies of most used keywords (KWIC, "Keyword In Context") by detecting the more important structures of its communication content. The Process of a Content Analysis According to Klaus Krippendorff (1980 and 2004), six questions must be addressed in every content analysis: 1) Which data are analyzed? 2) How are they defined? 3) What is the population from which they are drawn? 4) What is the context relative to which the data are analyzed? 5) What are the boundaries of the analysis? 6) What is the target of the inferences? According to Zipf Law, the assumption is that words and phrases mentioned most often are those reflecting important concerns in every communication. Therefore, quantitative content analysis starts with word frequencies, space measurements (column centimeters in the case of newspapers), time counts (for radio and television time) and keyword frequencies. However, content analysis extends far beyond plain word counts, e.g. with KWIC routines words can be analysed in their specific context to be disambiguated. Synonyms and homonyms can be isolated in accordance to linguistic properties of a language. Qualitatively it can involve any kind of analysis where communication content (speech, written text, interviews, images ...) is categorized and classified. While on its start with the first newspapers at the end of 19th century, it was done by manually measuring the amount of lines and space e.g. on newspapers. With the rise of common computing facilities like PCs, computer based methods of analysis are growing in popularity. Answers to open ended questions, newspaper articles, political party manifestoes, medical records or systematic observations in experiments can all be subject to systematic analysis of textual data. By having contents of communication available in form of machine readable texts, the input is analysed for frequencies and coded into categories for building up inferences. Weber (1990) notes: "To make valid inferences from the text, it is important that the classification procedure be reliable in the sense of being consistent: Different people should code the same text in the same way" (p. 12). The validity, Inter-coder reliability and Intra-coder reliability are subject to intense methodological research efforts over long years (see Krippendorf, 2004). One more distinction is between the manifest contents (of communication) and its latent meaning. "Manifest" describes what (an author or speaker) definitely has written, while latent meaning describes what an author intended to say/write. Normally, content analysis can only be applied on manifest contents, that are the words, sentences, texts in general. A further step in analysis is the distinction between dictionary-based (quantitative) approaches and qualitative approaches. Dictionary-based approaches set up a list of categories derived from the frequency list of words and control the distribution of words and their respective categories over the texts. While methods in quantitative content analysis in this way transform observations of found categories into quantitative statistical data, the qualitative content analysis focuses more on the intentionality and its implications. References - Bernard Berelson: Content Analysis in Communication Research. Glencoe, Ill: Free Press 1971 (first edition from 1952)
- Ian Budge/Hans-Dieter Klingemann et.al.: Mapping Policy Preferences. Estimates for Parties, Electors and Governments 1945-1998. Oxford 2001: Oxford University Press, ISBN 0199244006 (great example of application of content analysis methods in Political Science dealing with political parties and its impact on electoral systems).
- Klaus Krippendorf: Content Analysis: An Introduction to Its Methodology. 2nd edition, Thousand Oaks, CA: Sage 2004 (currently the most important book available, first edition was from 1980)
- Ole R. Holsti: Content Analysis for the Social Sciences and Humanities. Reading, Mass. 1969
- Carl W. Roberts (ed.): Text Analysis for the Social Sciences: Methods for Drawing Inferences from Texts and Transcripts. Mahwah, NJ: Lawrence Erlbaum 1997
- Robert Philip Weber: Basic Content Analysis. 2nd ed., Newbury Park, CA: Sage 1990 (recommended introductory reading)
External links - http://www.car.ua.edu/ (the seemingly most complete web resource on content analysis, with reading list of important publications, list of available software solutions and a mailing list for subscription)
- http://www.apb.cwc.net/homepage.htm (HAMLET software implementing routines of Multidimensional Scaling for comparison of similarities/proximities in textual data)
- On-line Content Analysis Tool
- http://ascweb.usc.edu/ (the Annenberg School of Communications, Los Angeles in the United States)
* http://www.essex.ac.uk/methods (the "Essex Summer School for Data Analysis and Data Collection", United Kingdom offers university-level education in social science methodology including content analysis methods).
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