Content analysis is a specific methodology, or research tool, which is used to determine the presence and extent of the presence of words, phrases, themes, or concepts within one or multiple bodies of text. The researcher breaks down their text into different words or themes, depending on their level of analysis, and thus ‘codes’ their data. Using this methodology, researchers can determine, analyse, and subsequently quantify their chosen subject focus, as well as investigate the presence, meanings, relationships and broader contextual connections of this. Once a researcher has conduced their analysis, inferences and conclusions can then be drawn about messages within the text and the broader framework in which it is found. These conclusions are not only limited to the specific body of text, but can be used to conclude information about the writer, audience, culture, and broader trends of the original piece, especially when placed within a broader existing framework.
Definition 1: “Any technique for making inferences by systematically and objectively identifying special characteristics of messages.” (Holsti, 1968)
Definition 2: “A research technique for the objective, systematic and quantitative description of the manifest content of communication.” (Berelson, 1952)
The list below shows the most notable examples of when content analysis should be used:
Discovering differences within the content of communication
Comparing actual content against desired content
Analysing open ended surveys and questions
Identifying key themes and characteristics of content
Detecting the existence of propaganda
Analysing patterns of behaviour within case studies
Describing historical trends within content
Content analysis should be undertaken if the researcher wants to investigate the content of a body of text or texts. If a researcher wants to understand more about the text, as well as wanting to contextualise it in relation to other texts, then content analysis is the easiest way to achieve this. Because humans must ‘code’ the data based on their needs, wants, and the research question, content analysis should be undertaken when data is not easily interpreted by computers, and requires human analysis to draw reliable conclusions.
The main benefits of using a content analysis (as opposed to the advantages, which will be discussed later) are that the reliability and validity of content analysis can be ensured through correct procedure (See Columbia Public Health, 2019).
Because content analysis requires human interpretation, the errors within the analysis can never be completely removed, but they can be minimised if the researcher considers three main areas. Firstly, the researcher must ensure complete stability within their coding of the data, ensuring that the same boundaries are used throughout. Secondly, the coding must be reproducible, so that other researchers can build on the data and so the user can draw from existing analysis. Both of these points can be ensured with strict definitions of coding and the criteria for coding. Thirdly, the accuracy of the data can be ensured through existing standards and statistics.
Equally, the validity of a content analysis can easily be ensured through correct practice and procedure. Firstly, the closeness of the categories studied must be taken into account, with synonyms and similar phrasing of the initial concept taken into consideration. Secondly, the level of interpretation for the conclusions must be appropriate to the data used – a content analysis of a single employee interview cannot be used to draw conclusions for the whole workplace, for example. Finally, the validity can guaranteed by contextualising them within an already established theory, and proving your results match the expected, or through a justifiable explanation should they differ.
The objective of content analysis is to expose and subsequently present insights, trends, relationships, and new information that is hidden within an existing body of text. This can be done through interpretation of the text once it has been broken down, or ‘coded’, into predetermined criteria (Clootrack, 2021).
Content analysis offers a methodology that can directly examine various forms of communication through the written word, and therefore can be used to analyse a wide range of data, including interview transcripts, open ended questionnaires, emails, and case studies to name a few. Content analysis is a broad methodology, and thus can allow for both qualitative and quantitative analysis, with the combination of results having the potential to offer a more reliable and valid conclusion. Because the text must be manually coded by the researcher, this gives the researcher great flexibility with choosing what they want to analyse. This also allows for the researcher to easily change or alter the focus of their research without significantly altering their methodology, especially if the analysis is done using computer software. Content analysis is an easily accessible methodology; its readily understood by those interpreting the data and those reading the paper, and requires few external resources to undertake. Finally, because content analysis allows for a direct look at specifics, it can be used to prove longer terms trends or abstracts when combined with an established framework (Weber, 1990; 9-13, 15-21).
However, there are numerous disadvantages of content analysis too. Firstly, a content analysis takes a large amount of time to complete correctly, and thus can only be used in situations where the researcher has the luxury of time. Equally, the time consumption combined with the level of complexity means that the analysis is subject to a higher risk of error than other methods; the level of complexity also requires new researchers learning this technique, thereby adding to the time cost and the likelihood of error.
Equally, content analyses are often without a solid theoretical foundation, especially as the user ‘codifies’ meanings within the content. While this allows for flexibility within the study, it also results in researchers drawing inferences and implied meaning where there is none. As such, a content analysis without an associated proven framework cannot inherently be said to be valid. Furthermore, if the coding undertaken by researchers without a high level of knowledge and skill in the research area, they are likely to make the analysis reductive, focusing on specific words or phrases without understanding the broader inferences. Finding a balance between being reductionist and liberal interpretation is not easy, and moving either way impacts the validity and reliability of the analysis. Finally, content analysis produces analysis on specific content, and thus is specific and exclusively temporal. It does not consider wider context, and cannot easily incorporate any change new changes in the status quo (Weber,1990; 9-13, 15-21).
Because content analysis can be applied to any piece of recorded communication, providing that it has been transcribed, content analysis is used in a wide variety of fields of study. It is most commonly used in marketing and media studies, literature analysis, public speaking and speech writing, ethnographies, cultural studies, sociology and anthropology, psychology, and political science. As well as the low requirements that are needed to undertake content analysis, it’s flexibility in being able to adapt to research any aspect of the text makes is another reason why it is so frequently used (Columbia State University, 2004; 6).
There are two main types of content analysis; conceptual analysis and relational analysis. The way a content analysis is completed depends upon the specific type of analysis conducted (See Columbia State University, 2004; 9-21).
Conceptual analysis: Best understood as attempting to establish the existence and or frequency of concepts within a text or texts.
The steps for undertaking a conceptual analysis are as follows:
1. Decide on your level of analysis
2. Decide on how many concepts to focus on
3. Choose your texts
4. Consider if you are examining the existence or frequency (or both) of a concept
5. Decide how to distinguish between concepts, and create strict parameters for inclusion/exclusion.
6. Decide how you will search for the main concept(s)
7. Establish what you will do with irrelevant information
8. Conduct your analysis
9. Analyse your results
Relational analysis: An analysis of the relationships surrounding a specific concept within a text or texts.
The steps to conducting a relational analysis are similar to that of a conceptual analysis:
1. Identify the question you are going to investigate
2. Choose your texts
3. Break the text down into categories, and code for words and patterns
4. Decide what you will do with irrelevant information
5. Explore the relationships between concepts
6. Code these relationships
7. Undertake statistical analysis, if required
8. Analyse your results.
Because content analysis is so varied and so flexible, there is not a standard template for people to work to as each content analysis is so different from another. Content analyses are based entirely on their chosen texts and the specific questions for study within the text, therefore a general template cannot be drawn up.
This is an example of content analysis whereby the analysis is undertaken on a group of people being interviewed on the question of how the format of media can warn people about the effects of nuclear power. The full title is “The Perception of Risk on Human Health from Nuclear Power among Swedish Young Adults: A Qualitative Study”.
Image 1: An example of content analysis (Zakaria, 2013)
The above shows part of an interview that has been broken down into codes, which are then related to the categories and themes of the speaker. These categories and themes can then be connected to other interviews, to examine how the body at large feel about nuclear power.
Berelson, B., 1952. Content analysis in communication research. Free Press
Clootrack, 2021. What is content analysis? Online, available at: https://clootrack.com/knowledge_base/what-is-content-analysis/#:~:text=The%20objective%20of%20content%20analysis,convert%20it%20into%20quantitative%20data, accessed 26/01/2021
Columbia Public Health, 2019. Population Health Methods; Content Analysis. Online, available at https://www.publichealth.columbia.edu/research/population-health-methods/content-analysis#:~:text=Content%20analysis%20is%20a%20research,words%2C%20themes%2C%20or%20concepts, accessed 26/01/2021
Holsti, O.R., 1968. Content analysis. The handbook of social psychology, 2, pp.596-692.
Weber, R.P., 1990. Basic content analysis (No. 49). Sage.
Zakaria, M., 2013.The Perception of Risk on Human Health from Nuclear Power among Swedish Young Adults: A Qualitative Study. 10.13140/RG.2.1.4774.0889. Online, available at: https://www.researchgate.net/figure/Example-of-content-analysis-in-this-study_tbl2_283548114, accessed 26/01/2021
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