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When analysing data, the researchers are typically looking for specific characteristics or traits. After all, they collect data in the first place to answer a question or test their hypothesis. So certain aspects of the data must reflect their tests – this is where content analysis comes in.
Content analysis is an observational analysis method used to identify words, themes, and concepts in qualitative data and convert them into quantitative data. This method follows a similar protocol as thematic analysis. Once done, inferential tests serve to learn more about patterns and trends in the data.
Researchers can use content analysis for various data collection methods as long as it generates qualitative data. Some examples of data collection methods include:
Interviews.
Speeches.
Diaries.
Letters.
There are several steps researchers must follow when using content analysis as a data analysis method. We describe these below.
Stage 1 – Researchers must prepare the data, i.e. transcribe it or format in some way to analyse it.
Stage 2 – Determining how to measure data, i.e., the units of measurement. These may be words, phrases, or topics highlighted each time they appear in the text.
Stage 3 – Determining codes and the coding system. The researcher identifies common themes in the phenomenon and decides what to include in their analysis. These are predefined words or themes highlighted each time they appear in the text. The themes should all be a unit of measurement for the variables under study in accordance with the hypothesis. The coding system essentially 'counts' each time a selected theme or word appears (the transformation to quantitative data).
The researcher can define these based on the data, previous researchers, and established theories. They will then find a way to code the text.
Stage 4 – Testing the coding sample on an excerpt of the text. It is similar to a pilot study and allows the researcher to determine if the coding system is a valid measure of the phenomenon and if adjustments are needed.
Stage 5 – Coding the text. Researchers convert the data from qualitative to quantitative.
Stage 6 – Checking the reliability of the coding system and the data. Researchers need to make sure that if the same data are coded again, similar results will be reported, indicating the high reliability of the system. To do so, it is good to have more than one person do the coding and compare their results to see if they are similar.
Stage 7 – Using the coded data for inferential statistics and concluding whether the data support or negate the proposed hypothesis.
Stage 8 – The final stage is to report the results and draw conclusions.
The following example is based on a research scenario that uses semi-structured interviews to investigate children's levels of aggression and loneliness six months after being adopted.
Stage 1 – The data must be prepared.
The first step is to transcribe the interview, i.e., to record every word or sentence and every sound and action made.
Stage 2 – Determining how to measure data.
In this case, the researchers decide to code for words and behaviours that indicate loneliness or aggression.
Stage 3 – Determining codes and the coding system.
The researcher must then determine in advance which words and behaviours they will highlight that indicate loneliness or anger. For example, participants raise their voices, curse, cry, or say phrases such as 'I feel lonely'. The coding system tallies how frequently the 'units' of the variables occur.
These are called units because they are a way to measure the variable.
Stage 4 – Testing the coding sample on an excerpt of the text.
The researchers use the answer to the first question as a pilot extract to determine if the coding system is a valid and reliable measure of the variables.
Stage 5 – Coding the text.
After adjusting the system and proving its reliability and validity, the entire data can be coded.
Stage 6 – Checking the reliability of the coding system and the data.
Then another researcher codes the transcript without looking at the other researcher's work. Once this is done, the coded data is checked to see if both researchers have reached the same conclusions.
Stage 7 and 8 – Using the coded data for inferential statistics, reporting the results and drawing conclusions.
In the final stages, the researchers transform the data to use it for inferential statistics. In this case, they analyse the participants' data to obtain an overall score for aggressiveness and loneliness. They conducted an independent t-test to compare these scores to those of children who were adopted and those who were not. Finally, the researchers must report the results and the conclusions drawn.
These are the basic steps of conducting a content analysis. However, they may vary from research to research as there is no standard procedure for conducting content analysis coding of online quantitative methods such as inferential statistics.
The use of content analysis is widespread in psychological research. There are many advantages to using this data analysis method. However, there are also disadvantages to consider when using this method. Researchers need to keep these in mind to determine if the data analysis method is appropriate.If researchers determine that the method is not appropriate for their research, using the wrong method may invalidate or omit important information in their results (e.g., if their research is better suited to another qualitative data analysis method, such as thematic analysis).
The strengths of content analysis are:
The weaknesses of content analysis are:
Researchers may omit vital data if it does not fit into the predetermined theme.
The context of the data is usually cut out, which can lead to misinterpretation and reduce the validity of the results. When we take out the context, the meaning can change drastically.
Content analysis is an analysis method for identifying words, themes, and concepts in qualitative data and converting them into quantitative data.
The two types of analysis differ in that content analysis quantifies qualitative data (converts it from qualitative to quantitative), while thematic analysis produces qualitative data.
Content analysis is an analysis method for identifying words, themes and concepts in qualitative data and transforming them into quantitative data. This method follows a similar protocol to thematic analysis. However, thematic analysis focuses on qualitative data.
There are eight steps to conducting content analysis:
Content analysis is carried out on qualitative data. However, its procedure involves transforming the qualitative data to quantitative.
Content analysis methodology needs to be written in thorough detail to replicate the research. In addition, the researcher needs to justify why they chose to do what they did to identify any potential biases.
The two types of analysis differ in that content analysis quantifies qualitative data (transforms it from qualitative to quantitative), whereas thematic analysis produces qualitative data.
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