This chapter was really complex and the story mutation problem could not be easily solved in the time frame allowed for delivering this chapter. However, what we discovered is truly amazing as it opens up a lot of questions. We did not want to draw any conclusion though, so we stopped our process right after the observation of the Paris attack disturbance and left that discussion open for our readers. Feel free to download our code base and study any breaking news and their potential impacts in what we define as an Equilibrium state. We are very much looking forward to hearing back from you and learning about your findings and different interpretations.

Surprisingly, we did not know anything about the Galaxy Note 7 fiasco before writing this chapter, and without the API created in the first section, the related articles would surely have been indistinguishable from the mass. De-duplicating content using  Simhash really helped us get a better overview of the world news events.

In the next chapter, we will try to detect abnormal tweets related to the US elections and the new president elect (Donald Trump). We will cover both Word2Vec algorithm and Stanford NLP for sentiment analysis.