Wouldn't it be nice if we could go out into the world with our clipboards, collect a bunch of information, and somehow have it all nicely computed and interpreted when we got home?
Unfortunately, that's not possible. We have to use our brains, resources, and efforts to not only go out there and find the answers to our questions but also to make sense of the information we find. One popular way of doing this is by conducting a content analysis.
- In this explanation, we will introduce the method of 'content analysis'.
- We'll start by defining 'content analysis', and discussing each of its relevant concepts one-by-one.
- After this, we will take a look at the basic stages involved in conducting a content analysis.
- Next, we will explore the various types of content analysis that can be conducted in the social sciences.
- Finally, we will close the explanation by evaluating the content analysis method's advantages and disadvantages.
What is the content analysis method?
Content analysis is a popular systematic approach to data interpretation that is widely used in the social sciences.
Defining 'content analysis'
Content analysis is not a method of data collection, but a way of interpreting data.
According to Merriam-Webster, content analysis is the "analysis of the manifest and latent content of a body of communicated material (such as a book or film) through a classification, tabulation, and evaluation of its key symbols and themes in order to ascertain its meaning and probable effect".
There are several aspects of this definition that we need to unpack to truly make sense of content analysis, how it's conducted, and why it is useful. Let's take a closer look...
First and foremost, it's important to note that this process is described as an analysis of content - meaning that it is not a method of collecting data. As such, researchers may need to use other primary or secondary research methods through which they will obtain data, that can then be interpreted using content analysis.
Primary research methods involve the collecting of data by the researcher who is carrying out the research themselves. Examples of primary research methods include interviews, observations, and surveys. In secondary research, the researcher analyses data that has already been collected.
You can find out more about these two forms of research in our dedicated StudySmarter explanations on "Primary Research" and "Secondary Research"!
The distinction between manifest and latent content is a crucial one. Sigmund Freud first identified these terms in his analysis of dreams. The term 'manifest content' refers to the exact, literal object that we see. However, the term 'latent content' refers to the hidden meaning behind the manifest content.
In sociological research, the communicated material chosen by the researcher will depend largely on their research aims and questions, as well as the types of resources that are available to them. Note that this content tends to be qualitative - it can include text, audio recordings, images, and videos.
The meaning and probable effects derived from content analysis also depend on the researcher's specific aims and questions. For example, a researcher might want to examine somebody's social development by studying their personal diaries. Alternatively, they may aim to study political trends by analysing government archives, newspapers, and Official Statistics. Another popular use of content analysis is to study media representation by examining the content, such as TV shows or news stories, and its effects on audiences.
What are the basic stages of content analysis?
As we have seen, there are many purposes and applications of the content analysis method in sociology. While there may be differences in the steps depending on the exact research aims, let's now look at the general steps that should be followed in every content analysis.
Conducting a content analysis
The basic steps to follow in content analysis are as follows:
1. First, the data needs to be collected and prepared. Of course, the process by which this is done will depend on the researcher's specific aims and resources.
For instance, if a researcher wants to analyse how students speak about their IGCSE experiences, they might choose to interview them and then transcribe those interviews so that they are ready for analysis. Another researcher might want to study how Muslims are represented in news articles in The Sun newspaper. Their data could then be issues of The Sun from the past year.
2. Next, depending on the researcher's aims, they must decide how they want to measure their data. Examples of measures include the use of particular adjectives, the types of images and colours used, or even what is not mentioned (in addition to what is mentioned).
3. Next is the coding step, arguably one of the most important in content analysis. Coding involves looking at the selected units of measurement and placing them into distinct categories that the researcher must identify.
The reason why the coding step is so important is that it sets guidelines that the researcher can follow to analyse all of their data consistently. The resulting document, which is called a coding frame, is also useful for other researchers to use so that they can replicate this research in the future.
4. Now that the researcher has established a coding frame, they can begin to code their data. Some researchers do this manually, while others use computer software that can help them out.
5. Next, the researcher must study their coded data and think about how it relates to their research aims and questions. They can then draw conclusions and report them to others.
6. Finally, a crucial last step of all research is to evaluate it once it is done. Researchers must reflect on their research methods and data, considering what was done well and what could be improved or elaborated in further research.
What are the various types of content analysis used in sociology?
There are various ways of conducting a sociological content analysis.
Researchers often distinguish between conceptual and relational content analyses.
The methods which researchers opt for can depend on many factors, such as the research aims, the available resources and the researcher's own theoretical stance.
Conceptual versus relational analysis
The most common distinction that is made within the method of content analysis distinguishes conceptual content analysis from relational content analysis.
Conceptual content analysis
Conceptual content analysis is usually the method which people think of when they talk about content analysis, generally. This involves choosing a particular concept and analysing selected content to test for it, specifically. The researcher will construct a coding frame and categories based on the chosen topic.
In a conceptual analysis, the instances of the chosen concept are usually identified in two ways:
explicit terms are more obvious, whereas
implicit terms depend on the interpretation and judgements of the researcher
Note that we made a similar distinction in our definition of content analysis, between manifest and latent content.
Imagine you are watching a brand-new Netflix series with your best friend. You both seem to enjoy the show, snacking on popcorn and laughing at all the jokes together. Once the series is complete, you ask your best friend what they thought. They tell you that they really enjoyed it, but that it would have been nice to see more people of colour in the main cast. You realise that you didn't notice this, and decide to go back to see for yourself.
You set aside a day to rewatch the series on your own, and make a note of all the White and non-White people who play main and side roles in the show, based on how much time screen time they have (explicit term) and the types of contributions that they make to the plot (implicit term). You aim to calculate a difference between the number of White main characters and non-White main characters throughout the series. The task that you now have on your hands is a conceptual content analysis.
Relational content analysis
A relational content analysis is quite similar to a conceptual analysis, except that there is an added step: examining the relationships between particular concepts.
A core assumption of relational analysis is that individual concepts don't have any meaning on their own - but that their meaning is created when they are combined and related with other concepts.
Imagine that you would like to explore the effect of the COVID-19 pandemic on people's feelings of loneliness. In this instance, the concept of 'loneliness' might not have much independent meaning. This could well be enhanced by combining it with the concept of 'isolation', which serves as an important link between the pandemic and loneliness.
Content analysis in sociology: advantages and disadvantages
As we know, each method of data collection and analysis comes with its own set of advantages and disadvantages. While these can differ on a case-by-case basis, there are some general evaluative points that we can consider when thinking about content analysis.
Strengths of content analysis
Identifying and counting up the instances of a particular topic means that the data generated from content analyses tend to be quantitative. This means that it becomes easier to identify trends and patterns.
Furthermore, creating a standardised coding frame makes this method highly replicable. Other researchers can apply the same guidelines to test the reliability and validity of results.
Considering explicit and implicit terms in a conceptual analysis makes for a more holistic analysis.
Limitations of content analysis
- On the other hand, researchers may experience a sense of bias where they actively search for content related to their concept, thereby overlooking content which does not line up with their research aims.
- Content analyses are vulnerable to the omission of context. By failing to consider the situational aspects of the concepts, the researcher misses a key component of sociological research. This can lead to inaccurate inferences, especially where the reliability of results is being cross-checked by other researchers who do not see the content in the same way.
Content Analysis in Sociology - Key takeaways
- Content analysis involves studying a piece of content for its themes, symbols and meanings.
- Content analysis involves collecting and selecting data, formulating a coding frame using the chosen analytical concepts, studying the selected content using this code, and drawing conclusions based on results.
- Researchers distinguish between conceptual and relational hypotheses, where the latter involves relating concepts to one another to establish meaning.
- Key advantages of content analysis include the ease with which it can be conducted, as well as the high level of standardisation and replicability that it enables.
- On the other hand, researchers who conduct content analyses are vulnerable to bias, which can lead to the exclusion of certain instances and concepts.
Explanations 
Exams 
Magazine 
