QUESTION 7 The "bag of words" approach to text mining is flawed in an important way when word order is ignored, the meaning of a particular sentence can completely shift. Given this major flaw, why do some data modelers continue to use it? With a "bag of words" approach, a text mining algorithm will be able to handle words in any language (assuming the language use a standard character script). The "bag of words" approach reduces the total number of words in a sentence, which means the volatile corpus will occupy less memory in RAM. A bag of words approach will ensure that the text data is normalized. The "bag of words" approach is much more computationally simple than an approach in which word order and syntax had to also be considered