As part of the analysis process, it is very common for SenseMaker practitioners to look at self-signification (patterns, sometimes statistics), but to leave narratives unused.
This tactic has been mainly driven by two factors:
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The notion that the meaning of words is relative and situational. This is true. But what is also true is that words are essential tools individuals use to communicate and dismissing them can lead to omitting important details and themes;
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The difficulty of automating analysis of unstructured and uncleaned text.
Documents on this page summarise our work on applying natural language processing (NLP) technique to SenseMaker narrative data. This work was also presented at the webinar (video here):
- Notebook.pdf - version of the notebook containing methodological underpinning, links to readings, outputs, and R script;
- Notebook.Rmd - file containing underlying R script in R Markdown format;
- Slides for the webinar.
Webinar materials are distributed under the MIT License. This is a permissive license that lets people do anything they want with the code as along as they provide attribution back to us and don’t hold us liable.
###You have three options for using the materials found on this page:
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You can download the materials by clicking on each link.
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You can "clone" repository, using the buttons found to the right side of your browser window as you view this repository. This is the button labelled "Clone in Desktop". If you do not have a git client installed on your system, you will need to get one here and also to make sure that git is installed. This is preferred, since you can refresh your clone as new content gets pushed to the webinar repository.
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Statically, you can choose the button on the right marked "Download zip" which will download the entire repository as a zip file.
You can also subscribe to the repository if you have a GitHub account, which will send you updates each time new changes are pushed to the repository.
You can read more about using GitHub with RStudio in Hadley Wickham's R Packages book Chapter 13.
If you decide to build on the material in this repository, the easiest way is to create a copy of the repo that you can own (called a fork), and then clone that fork on your own machine. Hadley Wickham's book (Chapter 13 mentioned above) describes the process in more detail.
Any contributions via pull requests are also more than welcome.