Tidy Text the Best Way to Utilize Analytics

August 10, 2017

Even though text mining is nothing new natural language processing seems to be the hot new analytics craze. In an effort to understand the value of each, along with the difference, and (most importantly) how to use either efficiently, O’Reilly interviewed text miners, Julia Silge and David Robinson, to learn about their approach.

When asked what advice they would give those drowning in data, they replied,

…our advice is that adopting tidy data principles is an effective strategy to approach text mining problems. The tidy text format keeps one token (typically a word) in each row, and keeps each variable (such as a document or chapter) in a column. When your data is tidy, you can use a common set of tools for exploring and visualizing them. This frees you from struggling to get your data into the right format for each task and instead lets you focus on the questions you want to ask.

The due admits text mining and natural language processing overlap in many areas but both are useful tools for different issues. They regulate text mining to statistical analysis and natural language processing to the relationship between computers and language. The difference may seem minute but with data mines exploding and companies drowning in data, such advice is crucial.

Catherine Lamsfuss, August 10, 2017


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