Coding and codes

Coding, or gathering material by topic, is a fundamental task in most qualitative projects. It tends to be a cumulative rather than a one-stage process, with the meaning and structure of your codes changing over time.

Where to start?

Coding is one of several techniques for making sense of your data—you can use it in conjunction with annotating, writing memos, linking and creating maps. The way you handle coding depends on your methodology and research design.

The way you approach the analysis of sources can depend on the

• Methodology you are using (if any)

• Amount and type of data you have

• Time available

NVivo does not prescribe an approach but provides the tools to let you work the way that suits you best. For example, if you have many sources or you have large dataset sources—make the most of NVivo's auto coding and query-based coding features. If you have a smaller number of sources that require close analysis—take advantage of the easy-to-use coding techniques.

You can create a code structure and then code your material at the 'ready-made' codes or you can create codes as you work through your source materials.

You could start with ‘broad-brush’ coding to organize your material into broad topic areas (you can use Text Search queries to help with this)—then explore the code for each topic and do more detailed coding:

Researchers working in methodologies such as phenomenology or discourse analysis may get straight into detailed coding (making codes as required) and then, later on, combine and group the codes into related categories.

You could combine these approaches or experiment to see what works best for you.

What is the purpose of coding?

Coding the content of your files can contribute to your analysis in the following important ways:

• The process of coding brings you closer to your data and 'forces' you to focus on your material—asking questions like; What is this about? Is it about more than one thing? How does it help me answer my research question?
• Coding lets you gather all the material about a topic in one place (for example, what did everyone say about water quality?)—this makes it easier to see patterns, contradictions and to develop theories.
• Coding facilitates the use of queries and visualizations allowing you to look for connections between themes and test your understanding. For example, you have a hunch that tourism impacts water quality—use a coding query to gather content coded to water quality where it is NEAR content coded to tourism and explore the connections.

How much coding should I do?

The amount of coding you do depends on your research design, the project time frame and the volume of data you are working with. A social scientist on a long term project may carefully code the content—looking for subtle themes and the connections between them. A brand manager may be more interested in analyzing broad topic areas in order to make rapid strategic decisions.

A researcher working with a large dataset (like the results of a survey) may use a combination of autocoding and Text Search queries to speed up the coding process.

You may not need to exhaustively code all your material. For example, if after working through twelve interviews you are not finding any new themes or ideas – you may have reached ‘saturation’. You could use Text Search queries to do some broad-brush coding in subsequent interviews.

Different types of coding

As you reflect on a piece of content, think about these different types of coding:

• Topic coding—What is the topic being discussed? For example, water quality, real estate development, tourism and so on. Text search queries can help you to search for topics in your material.
• Analytical coding—Once you have organized your material by topic, you can review the content of your codes and ask What is this content really about? Why is it interesting? How does it relate to my research question? Consider the meaning in context and express new ideas about the data. For example,  ideals vs reality or tension between developers and residents.
• Case coding—Who is speaking? What place, organization or other entity is being observed? You can code the material at a case and assign demographic attributes. Classify cases

Coding to multiple codes (co-occurring codes)

As you work with your files, consider coding content at multiple codes. For example, you could code Barbara’s comment at all of the codes shown on the left:

If you code all your interviews like this, then you can use queries to gather your material in different combinations. For example, show me

• All the content coded to water quality and development
• Negative attitudes about water quality
• What women said about water quality

Take time to reflect and 'code on'

After exploring and coding a file, take some time to reflect on what you have discovered. Display coding stripes to see your coding or run a report to see which codes have been used most often—how do these codes relate to each other? Make a map to explore the relationships and record your thoughts in a memo.

Coding is rarely a one-stage process. As you review the coded data at a code, you will often see ways to improve your coding—for example, you may want to:

• Include more of the context around coded content—for example, expand coding to include the whole sentence or paragraph.
• Remove some of the coded content by 'uncoding' it (especially useful if you used a Text Search query to do some broad-brush coding).
• Develop ideas by coding content to other codes— this process is termed 'coding-on'.
• Create or reorganize codes as you respond to what you are seeing in the coded data.

Coding references

Build an efficient code hierarchy

Take time out from coding to reflect on your codes and organize the themes that are emerging.  Reasons for keeping your codes organized include:

• Being able to find your codes easily saves time during the coding process.
• If you have trouble finding a code, you are less likely to use it consistently.
• You are more likely to lose or confuse ideas in an unwieldy code structure.

Here are some strategies for building an efficient code structure:

• Keep code names short and pertinent.
• Make sure a code only appears once in the whole hierarchy.
• Try not to combine concepts in a code. For example, instead of coding some text at skeptical attitudes about government policy, code it at both of these codes:
  • skeptical attitudes
  • government policy

    Remember that you can use queries to gather your coded content in all sorts of combinations—for example, find all content coded to the code skeptical attitudes AND at the code government policy.

• Try not to force codes into a hierarchy—if a code is not related to any other concept then leave it at the top level.
• Try not to nest more than 3 levels deep if you can help it.
• Make a code to gather 'great quotes'.
• Prune your codes regularly. Merge, reorganize, rename.

Use a codebook to manage codes

As you develop your thematic code structure, you can export or report on the codes and their descriptions to make a codebook. A codebook can clarify the meaning of the thematic codes so that you (or members in your team) can apply them to your data in a consistent manner.

If you have added information about the meaning of the code in the Description field in code properties, then you can:

• Export a codebook (in Word, Excel, Codebook Exchange Format) that lists the codes and their descriptions.
• Display the Description column in List View.  If you want to share this view with others, you can export the code hierarchy.