Text Analytics

The main focus of this textbook thus far has been the analysis of numerical data. Text analytics, introduced in this chapter, concerns itself with understanding and examining data in word formats, which tend to be more unstructured and therefore more complex. Text analytics uses tools such as those embedded in R in order to extract meaning from large amounts of word-based data. Two methods are described in this chapter: bag-of-words and natural language processing (NLP). This chapter is focused on the bag-of-words approach. The bag-of-words approach does not attribute meaning to the sequence of words. Its applications include clustering or segmentation of documents and sentiment analysis. Natural language processing uses the order and “type” of words to infer the meaning. Hence, NLP deals more with issues such as parts of speech.