Tweet Emotion: Realtime Tweet Pseudo-Analysis with PubNub Data Stream

"How is America feeling now?"

Visualized cartographic data of the emotional "state" of each state at any given moment

http://pubnub.github.io/tweet-emotion/

Pseudo-analysis

Positive or negative sentiments are loosely determined based on an analysis of keywords used in tweets

positiveWords = [
  'excellent', 'amazing', 'marvelous', 'magnificent', 
  'fabulous', 'astonishing', 'fantastic', 'peaceful', 
  'brilliant', 'glorious', 'cheerful', 'gracious', 
  ...
];

Process

1. using TopoJSON to display a US state map using d3.js
2. using PubNub JavaScript API to consume Twitter stream
3. colorizing the map by moods

GeoJSON

• Open standard format for encoding geographical features
• Written in JavaScript Object Notation
• Typically large file size

TopoJSON

• Extension of GeoJSON that encodes geospatial topology
• Compressed / Smaller size
• Tailored for only what you need

TopoJSON

Render TopoJSON with D3.js

var svg = d3.select('#map').append('svg')
  .attr('width', 900).attr('height', 550);

var path = d3.geo.path().projection(d3.geo.albersUsa());

Render TopoJSON with D3.js

var g = svg.append('g');

d3.json('us-states.json', function(error, topology) {
  g.selectAll('path')
    .data(topojson.feature(topology, 
      topology.objects.usStates).features)
    .enter().append('path')
    .attr('class', function(d){ 
      return 'states ' + d.properties.STATE_ABBR;} )
    .attr('d', path)
    .attr('fill', 'gray')
});

Getting Realtime Tweets from PubNub Stream

Getting Started with PubNub APIs

<script src="//cdn.pubnub.com/pubnub.min.js"></script>
		
var channel = 'pubnub-twitter';

var pubnub = PUBNUB.init({
  subscribe_key:'sub-c-78806dd4-42a6-11e4-aed8-02ee2ddab7fe'
});
		

Receiving Live JSON Data

To retrieve the live tweets, you simply use PubNub subscribe() API.

pubnub.subscribe({
  channel: channel,
  callback: processData
});
		

Pseudoanalyze Tweets

Create a mini dictionary that describes moods

var positiveWords = [
  'excellent', 'amazing', 'happy', 'magnificent', ':)', 
  ...
];
var negativeWords = [
  'unhappy', 'sorry', 'annoyed', 'dislike', 'anxious', ':(', 
  ...
];
		

Pseudoanalyze Tweets

See if these words are used in each tweet, in the callback function

function processData(data) {
  // looking for US data only for this demo
  if(data.place.country_code !== 'US') return;

  // Check if emotional words are used in the tweet
  if (positiveWords.some(function(v) { 
      return data.text.toLowerCase().indexOf(v) > 0; })) {
    displayData(data, positive);
  } else if
    ...
}
		

Pseudoanalyze Tweets

Create a mini dictionary that describes moods

var positiveWords = [
  'excellent', 'amazing', 'happy', 'magnificent', ':)', 
  ...
];
var negativeWords = [
  'unhappy', 'sorry', 'annoyed', 'dislike', 'anxious', ':(', 
  ...
];
		

Display Data on Map

function displayData(data, emotion) {
  var state = data.place.full_name.substring(
    city.lastIndexOf(',')+1).trim();
		
  if(document.querySelector('.'+state)) {
  var stateEl = document.querySelector('.'+state);
    
  // count
  tally[state] = (tally[state] || {positive:0, negative:0});
  tally[state][emotion] = (tally[state][emotion] || 0) + 1;

  ...
		

...cont'd

  // colorize svg path	
  stateEl.style.fill = (
    tally[state].positive > tally[state].negative) 
      ? 'pink' : 
      ((tally[state].positive < tally[state].negative) 
      ? 'turquoise' : 'beige'); 
    }	
  }
}
		

Full Article

blog.twitter.com

Thank you!

Tomomi Imura @ PubNub

pubnub.com
@pubnub
@girlie_mac
github.com/pubnub