@afkehaya We used the Rapid Automatic Keyword Extraction (RAKE) algorithm to extract keywords from posts name and tagline. And then filtered keywords manually. (For example, "app", "time", "world", "best", and etc were ignored.)
Hello Product Hunters!
Our dev team at Codementor made this side project over Christmas analyzing the most popular & fastest growing product categories of Product Hunt in 2015. We're really curious about what have become popular and if there are any interesting trends in 2015.
Video & photo apps have remained popular in 2015, while Apple Watch & Slack apps have arrived at the scene with the biggest growth.
Please check it out - would love your feedback!
@weitingliu@trantorliu This is SUPER cool!
Here's to 2016 :)
I sorted it by Growth score and Slack products grew over 1000% - Will be interesting to see how many more are launched since the release of the Slack App Directory
This is really awesome. Especially for predictive analysis when considering new products to create. Will be spending some time exploring this site.
The only issue I see is with the "book" section. I'm assuming it's supposed to be reading books (since ProductHunt has this section), but whatever algorithm used for pulling the books is pulling in products with book in the title, ie. Booking.js by Timekit & Bookstck
@melissamonteee Thank you for your feedback! We didn't notice this issue. However, we did notice that the word "watch" should be considered as a noun instead of verb. Let us figure out how to solve this. Thanks :)
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