Most researchers know very well that the coding of text data manually (using human coders who read the text and mark different codes) is very expensive both in terms of time that coders need to take and money needed to compensate them for this effort.
However, the major advantage of using human coding is their high understanding of complex meaning of text including sarcasms or jokes.
Usually at least two coders are required to code any type of text data and the calculation of inter-rater reliability or inter-rater agreement is a must. This statistic enables us to see how similarly any number of coders has coded the data, i.e., how often they have agreed on using the exact same codes.
Often even with the simplest codes the accuracy of human coding is low. No two human coders consistently code larger amounts of data the same way because of different interpretations of text or simply due to error. The latter is a reason why no single coder will code the same text data identically when done for the second time (perfect reliability for a single coder could be achieved in theory though, e.g., for very small datasets that can be proofread multiple times).
Another limitation is that human coders can only keep in their working memory a limited number of codes while reading the text. Finally, any change to the code will require repeating the entire coding process from the beginning. Because the process of manual coding of larger datasets is expensive and unreliable automated coding using computer software was introduced.
Automated or algorithm-based text coding solves many of the issues of human coding:
- it is fast (thousands of text comments can be read in seconds)
- cost-effective (automated coding should be always cheaper than human coding as it requires much less time)
- offers perfect consistency (same rules are applied every time without errors)
- an unlimited number of codes can be used in theory (some software might have limitations)
However, this process does also have disadvantages. As already mentioned above, humans are the only ones who can perfectly understand the complex meaning of text and simple algorithms are likely going to fail when trying to understand it (even though some new algorithms are under development recently, which can be almost as good as humans). Moreover, most software available on the market has low flexibility as codes cannot be known to or changed by the user.
Therefore, OdinText developers decided to let users guide the automated coding. Users can view and edit the default codes and dictionaries, create and upload their own, or build custom dictionaries based on the exploratory results provided by the automated analysis. The codes can be very complex and specific producing a good understanding of the meaning of text, which is the key goal of each text analytics software.
OdinText is a user-guided automated text analytics solution, which has aspects and benefits of both fully automated and human coding. It is fast, cost-effective, accurate, and allows for an unlimited number of codes like many other automated text analytics tools. However, OdinText surpasses the capabilities of other software by providing high flexibility and customization of codes/dictionaries and thus a better understanding of the meaning of text. Moreover, OdinText allows you to conduct statistical analyses and create visualizations of your data in the same software.
Try switching from human coding to user-guided automated coding and you will be pleasantly surprised how easy and powerful it is!
[Gosia is a Data Scientist at OdinText Inc. Experienced in text mining and predictive analytics, she is a Ph.D. with extensive research experience in mass media’s influence on cognition, emotions, and behavior. Please feel free to request additional information or an OdinText demo here.]
[NOTE: OdinText is NOT a tool for human assisted coding. It is a tool used by analysts for better and faster insights from mixed (structured and unstructured) data.]