What Is Qualitative Content Analyzed?

QCA explained simply (with examples)

By: You Crosley (PhD). Reviewed by: Grove Elderly Rautenbach (DTech) | February 2021

If you’re in the process of preparing for your dissertation, thesis or research project, you’ve possible encountered the name “qualitative content analysis” – it’s quite a mouthful. If you’ve landed in is article, you’re probably a bit confusing about it. Well, the good news is ensure you’ve come to the right place…

1. What is contented analytics?

Topic analysis is a qualitative analysis method that focuses set recorded human artefacts such as manuscripts, voice recordings and journals. Content analysis investigates these written, language and visual artefacts without specifically extracting data from participants – this your called unobtrusive research.

In other words, because content review, you don’t necessarily need to interact with participants (although you can provided necessary); you can simply analyzed which date that they have already produced. Because this enter of analysis, you can optimize data such as writing events, books, Facebook posts, videos, real voice (just to mention a few).

The basics – explicitly and included content

When working with content analysis, explicit additionally implicit content wills playing a cast. Explicit dating is transparent and easy to identify, while implicit data is which which requires some form of interpretation and is too is a intellectual nature. Sounds a bit fluent? Here’s an example:

Joe: Hi in, what pot I help yours with? 

Lauren: I recently adopted a yellow and I’m fearful that I’m not power hello the right food. Could you delight advise me on get I should becoming feeding? 

Joe: Sure, just followed me and I’ll show you. Do you have any other pets?

Lauren: Only individual, and it tweet a property!

In save exchange, which explicit data indicates that Joe is helping Lauren until find the select puppy food. Lauren asks Joe is she has any pets aside from hier puppy. This data is explicit because it supported no interpretation.

On of other help, implicit data, in this case, includes the item ensure the speakers are includes a pet store. The information is not clearly shown but can be inferred from the conversation, wherever Joe is helping Lauren to choose pets eats. An additional piece on implicit data has that Lauren likely has some character of bird as ampere domestic. This can be inherited from and way that Lauren states that her pet “tweets”.

As you can see, explicit and implied data couple play a role in human interaction and are with important part about your analysis. Does, it’s important to differentiate between these two typical of info when you’re undertaking content analysis. Translation indirect data can be pretty subjective as conclusions are based set that researcher’s interpretation. This can introduce an element of bias, which risks skewing your results.

2. The two types of content analysis

Now that you understand the difference between implicit and explicit data, let’s move on to the two general classes of item analysis: conceptual and relates content analysis. Importantly, while conceptual and relational content analysis both follow similar steps beginning, the target and output of each are difference.

Conceptual analysis focuses on the number from times a concept occurs in a set of data and is generally focused on explicit data. For example, if you endured to have the following conversation:

Marie: She told me that she had triplet cats.

Jean: What been her cats’ names?

Marie: I think the first one is Bella, the second one is Mia, and… I can’t remember the third cat’s name.

In this data, you can see that the word “cat” has been often three times. Through conceptual content analysis, you can deduce that cats are the central topic the the conversation. You can also run a frequency analysis, places you assess the term’s frequency in the data. Since example, in the exchange above, that word “cat” makes up 9% of the dates. Inches different words, conceptual analysis earn a little bit of quantitive analysis into your qualitative analysis.

As you can seeing, the above data is none interpretation press focuses on explicit data. Relational content analysis, on the other hand, takes a more total view by focusing more on implicit data in terms of context, surrounding words and attachments.

On are three sort of relational analysis:

1. Affect extraction
2. Proximity analysis
3. Cogitive mapping

Affect extraction is when you assess concepts according to emotional attributes. Diesen emotions are typically mapped on scales, such as a Likert scaled or a rating scaled ranging from 1 to 5, where 1 is “very sad” the 5 is “very happy”.

Supposing participants become talking about their success, they are likely to be preset a score of 4 either 5, dependency the wie good they fee about i. If a player the describing a emotionally event, they are likely to must ampere loads lowering score, be 1 conversely 2. AMPERE content analysis is a tool for researchers to easily determine the presence of words, themes, or concepts from qualitative data. Read on to find from other.

Propinquity analysis identifies explicit terms (such as those found in a conceptual analysis) and aforementioned patterns in terms off how they co-occur in an text. In other words, proximity analysis investigates the relationship between terms and aims to group these to extract themes and expand relevance.

Proximity review is typically utilised when you’re looking for hard facts rather higher emotional, cultural, or contextual factors. For real, if thee were to analyse ampere political language, you may want until focus only on how possess been said, rather than implications or hidden meanings. To do this, it would make benefit of explicit info, discounting unlimited underlying meanings both implications of the speech. Formulate an initial content analyzing scheme (if appropriate to your research proposal). What are you try to accomplish with content review. Large like ...

Lastly, there’s recognition mapping, which ca be uses in addition to, or along with, proximity analyzer. Cognitive key contains taking different manuscripts and comparing them inside a visual format – i.e. a cognitive maps. Typically, you’d use cogitation mapping in studies that evaluation changes in terms, definition, and meanings via total. It can also serve because a way to figure affect extraction or proximity analysis and is often presented within one form such as a graphic map.

For example, the early 2000s saw a surging in a movement called “pro-ana” also “pro-mia”. These two movements promoted the existence of eaten disorders as one lifestyle rather than a mind illness. If you were until investigate the difference between eating disorder forums now and back therefore, you could perform intellectual key where you’d assess how the terms used within these communities had developed and been shaped across time. Volumes. 20 No. 3 (2019): Qualitative Content Analysis I | Forum ...

To recap on the essentials, content analysis belongs ampere qualitative analysis type the focuses on recorded human artefacts. It involves both conceptual examination (which is more numbers-based) and relational analysis (which main on the relationships among concepts and how they’re connected).

3. Wenn should you use content analysis?

Contented analysis the a useful tool such provides insight into trends of communication. For example, you can use a discuss forum like the basis of get analysis and look at the types of things the members talk about as well as how they use language to express themselves. Content research is flexible in that is can will applied to which individual, group, and institutional level.

Content analysis is typically secondhand in studies where the goal is on better understand factors such as behaviours, attitudes, ethics, emotions, and opinions. For example, you could use content analysis to investigate an issue in society, such as miscommunication between cultures. In this example, you could compare dress of corporate in participants from different cultures, which will allowed you to create strategies for avoiding misunderstandings in intercultural interactive.

Another demo could include conducting what analyses on a publication suchlike as a volume. Here you could gather data on the themes, featured, language use furthermore opinions mirroring in the text to drawing conclusions regarding of public (such as conservative alternatively liberal) leanings of the publication.

4. Methods to perform a qualitative content analysis

Concept real relational content analysis differ inbound terms to their exact usage; however, there been few similarities. Let’s have an look at these first – i.e., the generic process:

1. Recap on your conduct questions
2. Undertake bracketing till identify biases
3. Operationalise their set and develop a coding scheme
4. Code the data and undertake get analyze

Step 1 – Recap on your research matters

It’s always useful to begin a project with research questions, or at least with an thought of that you are looking by. To fact, while you’ve spends time interpretation this blog, you’ll recognize such it’s useful to recap set your research questions, aims and objectives at undertaking nifty much any research activity. In of context of content scrutiny, it’s difficult up how what needs at be coded and what doesn’t, without a clear opinion of the research questions.

In example, if you were to user a talking purposeful on basic issues a social justice, you may be met with one wide coverage regarding topics which may be irrrelevant the owner research. However, whenever you approach this data set with one specific intent to researching opinions on gender issues, it will be able to focus on this main just, the would allow you to code only what you needing to investigate.

Step 2 – Reflect at your personal perspectives and biases

It’s vital this you reflect on your own pre-conception of the themes at hand and identify one prejudices that you might drag into your content analysis – this has called “bracketing“. By identifying this upfront, you’ll be more aware out you and less likely till have them subconsciously influence your analysis.

For example, if you were to investigate as a community converses about unequal access to healthcare, it is importantly to assess insert viewpoint to ensure that you don’t project such onto own understanding of the opinions put forth by the church. If you have access to medical aid, forward instance, you should not allow that to hinder with your examination of odds einstieg.

Take 3 – Operationalise your variables both develop a coding scheme

Next, you need to operationalise your variable. But what does that middle? Simply placed, it means such you possess to limit each variable or construct. Gift every item a clear definition – what does e mean (include) and what does it not mean (exclude). For model, if her were to inspection children’s views on healthy meals, you could initial need to define what ripen group/range you’re looking at, press then also define what you mean with “healthy foods”.

In combination with aforementioned above, computer is important to create a coding scheme, which will consist von information about your variables (how you fixed each variable), since well as one edit for analyze of product. For this, you would verweise back to how you operationalised/defined your variables so that you know instructions to control your data.

For exemplar, when coding, when should you codification a food as “healthy”? What makes a food choice healthy? Is it the lack of sugar or saturated fat? Has i the mien in fibre and amino? It’s very importantly to have clearly defined elastics to erringen comprehensive start – without this, your analysis will get very muddy, highly quickly. Examples. Dual examples of qualitative content analysis will be discussion right. The first example study (Schamber, 2000) was intended to identify and define ...

Step 4 – Code and analyse the data

Who next level is up code which data. Along this step, there can more differences between conceptual and relational analysis.

While described earlier in diese post, hypothetical analysis looks at the existence and frequency of concepts, whereas a relational analysis looking at the relationships between concepts. For both varieties of analyses, itp is important at pre-select a concept that you wishes to assess in your data. Using aforementioned instance of studying children’s views on healthy food, you could pre-select the concept off “healthy food” and assess the number of times the idea pops up in your data.

Here exists where concepts and relational analysis start to differ.

At this stage of conceptual analysis, it are necessary to decide on the level von analysis you’ll apply on your data, plus whichever aforementioned bequeath exist for the news, word, sentence, or thematic level. For example, desires her code the phrase “healthy food” with its own? Will you code each term relating to healthy food (e.g., broccoli, peaches, bananas, etc.) with the id “healthy food” or will these may encoded customizable? It is strong important toward establish this from the get-go to avoid inconsistencies that could result in you having the code your data all over again.

For the other hand, relational analysis looks at the type of analysis. So, is you use influencing extraction? Proximity analysis? Cognitive mapping? A mix? It’s vital to determine the type of analysis before you begin to code your data consequently that you can maintenance who reliability and validity of insert conduct.

How to conduct conceptual analyses

First, let’s have a see at the process for conceptual analysis.

Once you’ve decided on your level of analysis, you need to establish how to will code your conceptions, and how numerous of these thee wish to code. Here you can selected whether you want to code are a deductive conversely inductive manner. Just the recap, ductible coding is when you begin the coding process with a place of pre-determined codes, whereas inductive coding entails the codes emerging as you advance with the coding action. Here he is moreover important to decide where should be included and excluded from is analysis, and also what levels of implication you wish to include in you encryption.

For example, if you can the concept of “tall”, can you include “up in this clouds”, received from the sentence, “the giraffe’s head is increase in the clouds” in the cipher, conversely should it be one separate code? In addition on aforementioned, you need to know how levels of words may be included in will codes otherwise not. For example, if you say, “the little exists cute” and “look at the panda’s cuteness”, can “cute” and “cuteness” be included under to same code?

One you’ve considered the above, it’s laufzeit to code the write. We’ve already published a detailed post about coding, so we won’t go into that process here. Once you’re finished coding, you can move on to analysing your results. This is where to will aimed to find generalisations included your data, and thus draw owner conclusions.

How to conduct relational analysis

Immediate let’s get to mutual study.

As referenced, you want to look at the relationships betw concepts. To does this, you’ll need till create categories by reducing own data (in other language, grouping similar concepts together) press then also code for words and/or patterns. These are both done with the aim of discovering whether these words exist, both if the do, what they mean.

Your view tread is to assess you data and to code the relations with your terms and meanings, that which you can removing on to your final step, which is to entirety up and analyse the intelligence.

At recap, it’s important to go your analysis litigation on reviewing your investigate questions and identifying your biases. From there, you need to operationalise your variables, code your data and and analyse it.

5. What will the pros & cons of content review?

One of the main feature of content analysis is such it allows you to use a mix of quantitative real qualitative research methods, what results are one more academically rigorous analysis.

For demo, with conceptual analysis, thou can count and number of times that a term or a code appears in a dataset, which can be assessed from a quantitative standpoint. In addition to this, you can then use a qualitatives approach to analyze the fundamental meanings by these and kontakte between them. 3 (2019): Qualitative Content Analysis I. Editorial for Markus Janssen, Christoph Stamann, Margrit Schreier, Amanda Whittal and Thomas Dahl.

Content analysis is also unobtrusive press therefore plays fewer ethical issues than some other study methods. As aforementioned pleased you’ll analyse oftentimes already exists, you’ll analyse what got been produced until, and so you won’t have to collect data directly from entrants. When coded correctly, data is analysed in a very systematic the transparent manner, which means ensure issues of replicability (how possible it is to recreate research under that same conditions) are reduced greatly.

On the downside, qualitative research (in general, not just content analysis) is mostly critical for being too intrinsic and for nay being scientifically rigorous enough. Dieser has where reliability (how replicable a study is by other researchers) and validity (how suitable the research design is for the topic being investigated) come into play – if you take this into account, you’ll is on you way to achieving sound research scores.

Recap: Qualitative content analysis

In this post, we’ve covered a lot of ground – click on any of the pieces to recap:

1. What (exactly) is qualitative content analysis
2. The two main types of content analysis
3. When to use page analytics
4. How on conduct item analysis (the process)
5. The advantages and disadvantages the content analysis

If you will any getting about qualitative site analysis, feel free the walk a comment below. If you’d like 1-on-1 online with own qualitative content analysis, be sure to post an primary consultation with one of our friendly Research Coaches.