According to Cheryl Geisler, to understand the full complexity of language on need to:
- Understand language as multidimensional/multimodal
- Understand language as rhetorical
- Understand that language requires interpretation
- Understand that language interpretation depends of context
Coding is one of the most common analytical techniques in writing research. Geisler states that “Coding is the analytic task of assigning codes to nonnumeric data“. Most people tend to associate coding with ‘systematicity‘, which is fundamentally using an “articulated, orderly procedure.” The ability to systemize data whilst coding allows coders to create research that is replicable, aggregatable, and data supported.
Geisler argues that, coders should also consider the complexity of language as a factor when coding. While systematicity is at the heart of coding, solely viewing code as a quantitative analytic activity deviates from one of the premises of writing research: qualitative analysis. As such, we ignore softwares such as Microsoft Word when it comes to non numerical coding.
Fundamentally coding can be found in three out of four distinct forms of text analysis (Pollach 2012). Firstly in ‘human coding’, content is analyzed using a codebook in a way that attempts to be complete and unambiguous so as to “eliminate the individual differences among coders”. Secondly, in tradition qualitative analysis, words and phrases are either created or assigned in order to symbolize, summarize or capture some attribute of visual or language based data. Lastly, in text mining, through machine learning or otherwise, language can be used to code a foundation for the machine or bot to ‘learn’ (usually ‘object-oriented’) .
In all these cases, coders often give priority to systematicity of data. However, softwares such as Microsoft Office and MAXQDA are fundamentally built for a coder to consider the qualitative analysis of data, with the complexity of language in mind. The ways the systematize and analyze qualitative, language-based and visual data could take the form of a coding scheme, also known as a coding tree or a coding system. Understanding the complexities of language can often help us curate and optimize the efficiency of the code. This also means, that the coding software should enable the coder to support multiple dimensions to coding in order to conduct a complex analysis of language.
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