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Goals[ edit ] Content analysis is best understood as a broad family of techniques. Effective researchers choose techniques that best help them answer their substantive questions. That said, according to Klaus Krippendorffsix questions must be addressed in every content analysis: How are the data defined?
From what population are data drawn? What is the relevant context? What are the boundaries of the analysis? What is to be measured? The simplest and most objective form of content analysis considers unambiguous characteristics of the text such as word frequenciesthe page area taken by a newspaper column, or the duration of a radio or television program.
Analysis of simple word frequencies is limited because the meaning of a word depends on surrounding text.
Keyword In Context routines address this by placing words in their textual context. This helps resolve ambiguities such as those introduced by synonyms and homonyms. 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.
There are strong parallels between qualitative content analysis and thematic analysis. In its beginnings, using the first newspapers at the end of the 19th century, analysis was done manually by measuring the number of lines and amount of space given a subject.
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 manifestos, 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 analyzed for frequencies and coded into categories for building up inferences.
Reliability[ edit ] Robert Weber notes: Different people should code the same text in the same way".
Reliability of human coding is often measured using a statistical measure of inter-coder reliability or "the amount of agreement or correspondence among two or more coders". Hermeneutics and philology have long used content analysis to interpret sacred and profane texts and, in many cases, to attribute texts' authorship and authenticity.
The political scientist Harold Lasswell formulated the core questions of content analysis in its early-mid 20th-century mainstream version: Content analysis of textual big data produced by new mediaparticularly social media and mobile devices has become popular.
These approaches take a simplified view of language that ignores the complexity of semiosis, the process by which meaning is formed out of language.Sep 08, · At the Burnsides Laboratory at the University of Illinois, Champaign-Urbana, we carried out an analysis of the fatty acids (fat molecules) in grain-fed and grass-fed beef tallow.
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