There are lies, damn lies, and Amazon reviews. Why are so many Amazon or Yelp reviews bogus? Do they have bad data scientists who can't detect fraudulent reviews? No, they have unethical CEOs ready to do anything to make money short-term. And complaining about being unable to find real data scientists to solve their problems. This is a challenge for ethical data scientists who want to create value, but get punished by top management for not condoning their misdeeds.
In the case of Amazon, most items found on its website have excellent (but too many times, bogus) reviews, because they make money selling them - a big conflict of interest. In the case of Yelp, if your business is listed but you don't purchase advertising with them, your business will only get (bogus) bad reviews. Both cases are worth a class action lawsuit. Amazon will also generate (bogus) bad reviews (easy to detect - see below) against authors who do not comply with their ridiculous policies. As a data scientist, is it worth working for such companies?
In the case of Amazon, bad reviews can also arise because of publisher wars - Wiley against Elsevier or O'Reilly - or because of disruptive content, like proving that SQRT(2) is an irrational number. The author of the proof, Aristotle, was murdered 2,000 years ago for stating and proving this fact; interestingly, an algorithm to generate all digits of this number was recently found. Even today, things haven't changed.
Anyway, here are two of these bogus reviews that any working brain could easily detect - no need for advanced data science algorithms! Dr Granville has promised to add detection of bogus reviews as a project in our DSA program.
Example of bogus Amazon reviews
Note how short these reviews are, providing no explanations, no facts.
I think it is time to build a new Yelp or ignore both Amazon and Yelp reviews. These companies have many other problems, see e.g.