tweet analysis funtimes

gistfile1.txt

var Twitter = require('twitter');
var analyze = require('Sentimental').analyze
var R = require('ramda')

var client = new Twitter({
  consumer_key: '',
  consumer_secret: '',
  access_token_key: '',
  access_token_secret: ''
});
 
var params = {screen_name: 'netflix', count: 200};
client.get('statuses/user_timeline', params, function(error, tweets, response){
  if (error) return

	var ts = R.map(R.pick([ 'retweet_count', 'text' ]), tweets)

	var getCount = R.prop('retweet_count')
	var getText = R.prop('text')

	var ave = function(nums) {
		return R.reduce(R.add, 0, nums) / nums.length
	}

	var counts = R.map(getCount, ts)
	var aveCount = ave(counts)
	var wasWellReceived = R.compose(R.gte(aveCount), getCount)
	var rateResponses = R.partition(wasWellReceived)

	var analyzeAll = R.map(R.compose(analyze, getText))

	var analysis = analyzeAll(ts)

	var zipped = R.zip(ts, analysis)

	var bySentiment = R.reduce(function(memo, v, i) {
		if (!v[1].score) return memo
		return memo.concat(R.merge(v[0], { x: v[1].score > 0, _raw: v[1].score }))
	}, [], zipped)

	var byQuote = R.reduce(function(memo, v, i) {
		return memo.concat(R.merge(v, { x: /"[^"]+"/.test(v.text) }))
	}, [], ts)

	var sentimentParts = R.partition(R.prop('x'), bySentiment)
	var quoteParts = R.partition(R.prop('x'), byQuote)

	var yepNopeAves = R.compose(R.map(ave), R.map(R.map(getCount)))

	var sentimentAves = yepNopeAves(sentimentParts)
	var quoteAves = yepNopeAves(quoteParts)

	console.log('For positive sentiment: ', sentimentAves[0])
	console.log('For negative sentiment: ', sentimentAves[1])

	console.log('-------------------')

	console.warn('Result: ', sentimentAves[0] > sentimentAves[1] ? 'positive ' : 'negative ', 'wins!')

	console.log('-------------------')

	console.log('For quotes: ', quoteAves[0])
	console.log('For non-quotes: ', quoteAves[1])

	console.log('-------------------')

	console.warn('Result: ', quoteAves[0] > quoteAves[1] ? 'quotes ' : 'non-quote ', 'wins!')

});