Word Clouds and Qualitative Data Analysis

With the overwhelming amount of data available on the internet sphere, it becomes imperative to find tools that will help in organizing the data for specific purposes. There are various quantitative and qualitative research methods available for the same. Word clouds are one such qualitative analysis method. 

What is a word cloud?

Word cloud, also known as a tag cloud, is the pictorial representation of word frequency which gives more prominence to words appearing more often in a particular text. The more frequently the word appears in the source text, the larger the word will be in the word cloud graphic. 

The type of data visualization word clouds helps data analysts in qualitative research design and further assists them in compiling qualitative data and turning it into quantitative data in statistics. 

We have understood that word clouds assist in qualitative analysis methods, but what exactly is qualitative data? What are the approaches and methods involved in it? Let’s take a deeper look. 

What is qualitative data?

Qualitative data is any type of data which describes. In other words, any data which can be presented through feelings or words rather than numerical values is called qualitative data. 

The result of qualitative analysis methods cannot be categorically measured as it is in a descriptive form. It makes a reference to the words or labels that are used to describe traits or characteristics. However, there are certain tools like word clouds that can help in organizing the data and making it accessible. 

What are the types of qualitative data?

The major types of qualitative data are: 

• binary data – represented numerically using ones and zeroes,
• nominal data – also called nominal scaled data or named, labelled data, any type of data which labels something without giving it a specific numerical value, and 
• ordinal data – when qualitative data is organized in a particular order or on a scaled range. 

When should you use qualitative data and qualitative research methods? 

You should use qualitative research methods for data analysis when you need to deduce a particular trend of characteristics or to set parameters for observing larger data sets. Qualitative analysis methods help data analysts to turn qualitative data into quantitative data in statistics to a certain extent. 

You can use qualitative data to answer questions like what your target audience is, what kind of issues your establishment is facing, or focus areas on finding a solution. 

Qualitative data is often used to understand the language used by consumers. Hence, qualitative research design tools like word cloud are helpful in analyzing such data. 

What are the approaches to qualitative data?

There are five common approaches to qualitative data: 

• ethnography,
• narrative,
• phenomenological,
• grounded theory, and
• case study.

These five common approaches usually use similar data collection methods. What differentiates them is the purpose of the study. The differences between the approaches can be slightly blurry, so let’s understand them in a bit more detail. 

What do the 5 qualitative approaches explain?

• Ethnographic – Ethnographic approach to qualitative data is one of the most familiar and applied types of qualitative research methods, particularly used in qualitative research design by UX professionals. In this approach, the researcher immerses in the target group or individuals’ environment to become familiar with their cultures, themes, goals, motivations, and challenges. Instead of relying on qualitative research methodology examples like surveys or interviews, the researcher experiences and understands the environment first-hand like a participant observer.
• Narrative – The narrative approach to qualitative data compiles a chain of events in sequence, generally from just one or two participants, to construct a cohesive story. The researcher reads documents, looks for themes, and conducts interviews to determine how an individual story can depict the larger influences that shaped it. The final narrative doesn’t necessarily have to be in sequential order. It can be presented in the form of a story according to the theme, can present conflicting stories to highlight the tensions and the challenges which can lead to solutions. Qualitative research design tools like word cloud can aid in the process.
• Phenomenological – We use the phenomenological approach to qualitative data to describe an activity, event, or phenomenon. In this approach, researchers utilize a combination of qualitative research methodology examples like reading documents, conducting interviews, watching videos, or visiting events to understand the meaning the participants place on what is being analyzed. In a phenomenological data study, five to twenty-five interviews are conducted to find common themes and to form an adequate data set. We can use quantifiable visualization tools like the word cloud to present this data.
• Grounded theory – While the phenomenological approach describes the basic themes of the event, the grounded theory approach to qualitative data looks to provide a theory or explanation behind those events. Documents and interviews are used to build a theory based on the given data set. The grounded theory approach can help in aiding qualitative research design decisions better, based on a solid explanation of how a target group of users presently perform a task or use a product.
• Case study – The case study approach to qualitative data involves an in-depth understanding of a study or an event using numerous types of data sources. Case studies can describe an event, or they can be explanatory or exploratory. Tools like the word cloud can be used to depict the keywords that come up in the study graphically.

What are the 3 methods used in the qualitative approach to data?

Each of the five qualitative data approaches involve the use of one or more qualitative research methods. The three most common types of qualitative data research methods are: 

• Observation – researchers record what they have seen, heard or encountered in the form of detailed notes. Observation is typically an inductive data collection approach and is used when the researcher has little or no idea of the phenomenon being studied, 
• Interviews – here, data collection occurs through researchers personally asking questions to the participants in one-on-one conversations. Interviews are the most frequently used qualitative research methods for deductive data collection, and
• Focus groups – in focus groups, the participants are asked questions to generate a discussion on the topic. Focus groups usually consist of six to ten people. Participants are selected depending on the aim of the study and the type of qualitative data required. 

Apart from these three common methods, surveys and secondary qualitative research methodology examples like documents, images, audio, and video recordings are also used. 

What are the benefits of using word clouds?

Word clouds are extremely easy to use. Moreover, they are feasible and inexpensive. This makes them an immensely handy tool to use in qualitative data research and analysis. 

What are some challenges you can encounter while using word clouds?

Some challenges data analysts may face while using word clouds for qualitative data collection are as follows:

• The graphic visualization of the word cloud gives emphasis to the frequency of a particular word rather than its importance in the source text. 
• Word clouds don’t give the proper context of the source. Different words used for the same concept are presented without any connection. 

As a result of these limitations, word clouds are usually used for exploratory qualitative analysis methods for deducing data.