text mining

 Some of the most important data that we have are large quantities of text data. Text data includes books, articles, blog posts, social media posts, emails, reports, journals and diaries, shopping lists, etc. etc. etc. This data is unstructured and can be massive. We have software tools available to help us make sense out of large quantities of text data. When we use software to analyze and try to make sense out of text data, we call this text mining. A practical example of this is chat bots. Chat bots utilize algorithms to try to make sense out of what the user types so it can select an appropriate response. In this assignment we will explore the text mining strategies of looking at word frequency and occurrences. Other methods beyond the scope of this class include part of speech tagging and machine learning.