Mastering Data Mining with Python – Find patterns hidden in your data

Summary

After finishing this chapter, we now have a functional understanding of how sentiment analysis works, and we have compared many different strategies that the mainstream sentiment analysis tools use to accomplish this goal. We paid special attention to the Vader tool which comes as standard with the Python NLTK, since it is well-tested and straightforward to use. To learn how to use its sentiment intensity scoring system, we calculated the sentiment for a few different real-world datasets, both messy chat data and somewhat more structured e-mail data.

In the next chapter, we will continue to hone our skills in text mining, but instead of looking at the emotion conveyed by an entire sentence, we will focus our attention on locating entities ...