“Thinking is classifying” wrote Georges Clémenceau*. This tells, in simple words, everything about the obsession of the human mind to keep things tidy. No surprise we ask computers a little help here and there. Is this email spam? Is this online user human? Is this text written by that author? Training machines to put things into the boxes created by our human mind is called supervised learning and it can be very lucrative. But what about the more philosophical cases where machines make their own boxes? Can we reverse the process and put things in boxes created by computers? Unsupervised learning, as it is called, creates a lot of interesting problems where we, humans, are left wondering whether the boxes make any sense.
The mother of all classification techniques is undisputedly Principal Component Analysis (PCA). But let me reassure those who hate PCA and those who never heard of it: I will just touch the surface, and then very briefly. PCA automatically arranges similar items close to each other on a plane. The rest is up to you. Similarity, in particular, depends on a bunch of arbitrary features, size, height, number of legs... In a classical introductory...
This is it! I have been preparing this post for a very long time and I will finally tell you what is so special about IMDB user 2467618, also known as planktonrules. But first, let me take you back where we left off in this post series on IMDB reviews.
In the first post I analyzed the style of IMDB reviews to learn which features best predict the grade given to a movie (a kind of analysis known as feature extraction). Surprisingly, the puncutation and the length of the review are more informative than the vocabulary. Reviews that give a medium mark (i.e. around 5/10) are longer and thus contain more full stops and commas.
Why would reviewers spend more time on a movie rated 5/10 than on a movie rated 10/10? There is at least two possibilities, which are not mutually exclusive. Perhaps the absence of a strong emotional response (good or bad) makes the reviewer more descriptive. Alternatively, the reviewers who give extreme marks may not be the same as those who give medium marks. The underlying question is how much does the style of a single reviewer change with his/her...