Text mining can be fun and applied to practical day to day tasks. One example of text mining is matching a resume to a job description. A resume or online profile can be compared to job postings in order to check commonly used words for example. That will help understanding if a CV is close enough to a job description. If you want to learn more about text analytics, I would suggest following link https://www.softwareadvice.com/resources/what-is-text-analytics/

If you want an easy way to see how to compare your resume or profile to a job description and see a comparison of commonly used words, you have a couple of options. You can use word cloud applications that are free on the web and upload your CV and then the job description. This will give you an view on how both compare visually. For example you can check this article that gives you some advice on how to do this: http://cultivitae.com/2018/04/01/word-cloud-generator/.

Another way is to use a bit more sophisticated tools ( for example R library function pyramidplot) that will show you the comparison of most used words in a graph, so for example I took my LinkedIn profile and compared it with a job description for a CIO position in banking. I removed few common words that were not relevant like page, years,  including and others.

This gives you a way to quickly check if your CV does have the right focus and has a chance to go through the first checks ( automated or not). Obviously tweaking your CV to have the same most used words does not give you a guarantee you will be selected or even hired, but gives you an idea if the job you are looking for is close or far away from your current profile focused words.

This is pretty fun application of text mining.

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