Describe the steps necessary when performing a content analysis.

Question

What will be an ideal response?

Answer 1

The goal of a content analysis is to develop inferences from text (Weber, 1985). You could think of a content analysis as a “survey” of some documents or other records of prior communication. In fact, a content analysis is a survey designed with closed-ended responses so that it produces quantitative data that can be analyzed statistically.
Content analysis bears some similarities to qualitative data analysis because it involves coding and categorizing text, discovering relationships among constructs identified in the text, and a statistical analysis of those findings. Content analysis is also similar to secondary data analysis because it involves taking data or text that already exists and subjecting it to a new form of analysis; however, unlike secondary analysis of previously collected quantitative data, content analysis also involves sampling and measurement of primary data. Content analysis techniques can be used with all forms of messages, including visual images, sounds, and interaction patterns as well as written text (Neuendorf, 2002).
Identifying a Population of Documents or Other Textual Sources: The population of documents that is selected for analysis should be appropriate to the research question of interest. Words or other features of these units are then coded in order to measure the variables involved in the research question. The content analysis involves the following steps or stages (Weber, 1985).
1. Identify a population of documents or other textual sources for study. This population should be selected for its appropriateness to the research question of interest. Perhaps the population will be all newspapers published in the United States, college student newspapers, nomination speeches at political party conventions, or State of the Nation speeches by national leaders.
2. Determine the units of analysis. These could be newspaper articles, whole newspapers, television episodes, or political conventions.
3. Select a sample of units from the population. The most basic strategy might be a simple random sample of documents. However, a stratified sample might be needed to ensure adequate representation of community newspapers in large and small cities, of weekday and Sunday papers, or of political speeches during election years and in off years.
4. Design coding procedures for the variables to be measured. This requires deciding what unit of text to code, such as words, sentences, paragraphs, or newspaper pages. Then, the categories into which the units are to be coded must be defined. These categories may be broad, such as supports democracy, or narrow, such as supports universal suffrage.
5. Test and refine the coding procedures. Clear instructions and careful training of coders are essential.
6. Base statistical analyses on counting occurrences of particular items. These could be words, themes, or phrases. You will also need to test relations between different variables.
Developing reliable and valid coding procedures is not an easy task. The meaning of words and phrases is often ambiguous. As a result, coding procedures cannot simply categorize and count words; text segments in which the words are embedded must also be inspected before codes are finalized. Because different coders may perceive different meanings in the same text segments, explicit coding rules are required to ensure coding consistency. Special dictionaries can be developed to keep track of how the categories of interest are defined in the study (Weber, 1985).
After coding procedures are developed, their reliability should be assessed by comparing different coders’ codes for the same variables. The criteria for judging quantitative content analyses of text reflect the same standards of validity applied to data collected with other quantitative methods. We must review the sampling approach, the reliability and validity of the measures, and the controls used to strengthen any causal conclusions.