score_subreddit: Computes the Flesch-Kincaid grade level of the last 25 comments of the given subreddits.

score_subreddit.rb

#
# Usage: ruby score_subreddit.rb <list of subreddits>
#
# Computes the Flesch-Kincaid grade level of the last 25 comments of the given subreddits.
# 
# For example:
# > ruby score_subreddit.rb science worldnews funny
# science: 8.33
# worldnews: 9.71
# funny: 5.32
#

require 'curb'
require 'json'
require 'cgi'
require 'nokogiri'

# taken from https://github.com/matstc/text-analysis-utils/blob/master/bin/readability-of
def flesch_kincaid_grade_level(text)
	def vowels w
		w.split(/b|c|d|f|g|h|j|k|l|m|n|p|q|r|s|t|v|w|z/i).reject{|s|s.empty?}
	end

	words = text.split(" ").size.to_f
	sentences = text.split(/\.|\?|!/).reject{|s| s.strip.empty?}.size.to_f
	syllables = text.split(" ").inject([]){|sum, w| sum + vowels(w)}
	syllables = syllables.size.to_f * 0.9 # for silent vowels

	grade_level = (0.39 * (words / sentences) + 11.8 * (syllables / words) - 15.59)
	return (grade_level * 100).floor() / 100.0
end

def score_subreddit(subreddit)
	response = Curl::Easy.perform("http://www.reddit.com/r/#{ subreddit }/comments.json")
	response_json = JSON.parse(response.body_str)

	text = ""
	response_json['data']['children'].each{ |comment|
		text += Nokogiri::HTML(CGI.unescapeHTML(comment['data']['body_html'])).text
	}

	return flesch_kincaid_grade_level(text)
end

ARGV.each do |subreddit|
  puts "#{subreddit}: #{score_subreddit(subreddit)}"
end