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PHP Twitter sentiment analysis


The task is to setup an online Twitter Sentiment Analysis tool using Twitter Streaming API. There is no specific guidline. The tool should determine if a tweet is positive or negative. Preferably with a graph. With detailed notes explaining the step-by-step implementation of the process – very important for the oral presentation. Preferable language is php, but can use any only if php is not possible.


Twitter sentimental analyser


  • The aim of the application is to fetch real time tweets for a particular hashtag and then analyse the sentiment and decide the polarity of the tweet.
  • Twitter API is used to fetch the real time tweets from the twitter. The sentiments are decided using the naïve bayes approach.
  • For checking the accuracy of the calculated sentiment , alchemy API is used, which uses machine learning for analysing the sentiment and has an accuracy of 83% on an average.

Running the Code:

  • Set the $tweetcount parameter in index.php to define the number of tweets to be fetched .
  • run index.php file in browser.

Third party API’s used:

  • twitter API: to fetch real time tweets from twitter.

  • alchemy api: to check the accuracy of calculated sentiment against machine learning response.

  • Highchart.js: for generating charts

Technologies used:

Languages: html, php, css, javascript

Algorithms: machine learning, naïve bayes classification

Problems faced:

  • First major problem faced was to decide which algorithm to use. Machine learning would have been the most accurate. But since we don’t have have data to make the algorithm learn and also for learning we need huge amount of data which is not available and it will take too much time to manually generate the time. So the next best algorithm that was feasible was naïve bayes classification.
  • Secondly, there is no way to precisely check the accuracy. The best machine learning sentimental classifier available on the internet(alchemy api) has an accuracy of 83% only.

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<!DOCTYPE html>

<meta http-equiv=”Cache-Control” content=”no-cache”>
<meta http-equiv=”Content-Type” content=”text/html; charset=utf-8″>
<meta http-equiv=”Lang” content=”en”>
<script src=”jquery.min.js”></script>
<script src=”highcharts.js”></script>

<title>Twitter Sentiment Analysis Demo</title>
<h1>Twitter Sentiment Analysis</h1>
<p>Type your keyword below to perform Sentiment Analysis on Twitter Results:</p>
<form method=”GET”>
<label>Keyword: </label> <input type=”text” name=”q” />
<input type=”submit” />


if(isset($_GET[‘q’]) && $_GET[‘q’]!=) {

//Search Tweets parameters as described at

<h1>Results for “<?php echo $_GET[‘q’]; ?>“</h1>
<table border=”1″>
<td>Twitter Link</td>
<!– <td>Expected Sentiment_datum</td>–>
<td>Expected Sentiment_alchemy</td>
<td>Calculated sentiment</td>
foreach($results as $tweet) {







if($tweet[‘sentiment’]==‘neutral’ && $tweet[‘calculated’]==‘neu’){
if($tweet[‘sentiment’]==‘negative’ && $tweet[‘calculated’]==‘neg’){
if($tweet[‘sentiment’]==‘positive’ && $tweet[‘calculated’]==‘pos’){
<tr style=”background:<?php echo $color; ?>;”>
<td><?php echo $tweet[‘id’]; ?></td>
<td><?php echo $tweet[‘user’]; ?></td>
<td><?php echo $tweet[‘text’]; ?></td>
<td><a href=”<?php echo $tweet[‘url’]; ?>” target=”_blank”>View</a></td>
<!–<td><?php //echo $tweet[‘sentimentd’]; ?></td>–>
<td><?php echo $tweet[‘sentiment’]; ?></td>
<td><?php echo $tweet[‘calculated’]; ?></td>
<p>Total number of tweets: <?php echo $count1; ?></p>
<p>Number of sentiments correctly calculated: <?php echo $count; ?></p>
<p>Accuracy: <?php echo $count*100/$count1;?>%</p>

var a=<?php echo $positive1; ?>;
var b=<?php echo $positive2; ?>;
var n=<?php echo $neutral1; ?>;
var m=<?php echo $neutral2; ?>;
var c=<?php echo $negative1; ?>;
var d=<?php echo $negative2; ?>;

<div id=”container” style=”min-width: 310px; height: 400px; margin: 0 auto”></div>
<script type=”text/javascript”>
$(function () {
chart: {
type: ‘column’
title: {
text: ‘twitter sentimental analizer’
subtitle: {
text: ‘result’
xAxis: {
categories: [
yAxis: {
min: 0,
title: {
text: ‘tweets’
tooltip: {
headerFormat: ‘<span style=”font-size:10px”>{point.key}</span><table>’,
pointFormat: ‘<tr><td style=”color:{series.color};padding:0″>{}: </td>’ +
‘<td style=”padding:0″><b>{point.y:.1f} mm</b></td></tr>’,
footerFormat: ‘</table>’,
shared: true,
useHTML: true
plotOptions: {
column: {
pointPadding: 0.2,
borderWidth: 0
series: [{
name: ‘positive’,
data: [a, b]

name: ‘neutral’,
data: [n, m]

name: ‘negative’,

[c, d]


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require_once __DIR__ . '/../autoload.php';
class TwitterSentimentAnalysis {

    protected $datumbox_api_key; //Your Datumbox API Key. Get it from

    protected $consumer_key; //Your Twitter Consumer Key. Get it from
    protected $consumer_secret; //Your Twitter Consumer Secret. Get it from
    protected $access_key; //Your Twitter Access Key. Get it from
    protected $access_secret; //Your Twitter Access Secret. Get it from

    * The constructor of the class
    * @param string $datumbox_api_key   Your Datumbox API Key
    * @param string $consumer_key       Your Twitter Consumer Key
    * @param string $consumer_secret    Your Twitter Consumer Secret
    * @param string $access_key         Your Twitter Access Key
    * @param string $access_secret      Your Twitter Access Secret
    * @return TwitterSentimentAnalysis  
    public function __construct($datumbox_api_key, $consumer_key, $consumer_secret, $access_key, $access_secret){


    * This function fetches the twitter list and evaluates their sentiment
    * @param array $twitterSearchParams The Twitter Search Parameters that are passed to Twitter API. Read more here
    * @return array
    public function sentimentAnalysis($twitterSearchParams) {

        return $this->findSentiment($tweets);

    * Calls the Search/tweets method of the Twitter API for particular Twitter Search Parameters and returns the list of tweets that match the search criteria.
    * @param mixed $twitterSearchParams The Twitter Search Parameters that are passed to Twitter API. Read more here
    * @return array $tweets
    protected function getTweets($twitterSearchParams) {
        $Client = new TwitterApiClient(); //Use the TwitterAPIClient
        $Client->set_oauth ($this->consumer_key, $this->consumer_secret, $this->access_key, $this->access_secret);

        $tweets = $Client->call('search/tweets', $twitterSearchParams, 'GET' ); //call the service and get the list of tweets


        return $tweets;

    protected function findSentiment($tweets) {
        //$DatumboxAPI = new DatumboxAPI($this->datumbox_api_key); //initialize the DatumboxAPI client
        $analyse=new alchemyAPI();
        $Calculatedsentiment = new \PHPInsight\Sentiment();
        foreach($tweets['statuses'] as $tweet) { //foreach of the tweets that we received
            if(isset($tweet['metadata']['iso_language_code']) && $tweet['metadata']['iso_language_code']=='en') { //perform sentiment analysis only for the English Tweets
                $sentimentd='neutral';//$DatumboxAPI->TwitterSentimentAnalysis($tweet['text']); //call Datumbox service to get the sentiment
                $scores = $Calculatedsentiment->score($tweet['text']);
                $class = $Calculatedsentiment->categorise($tweet['text']);
                if($response['status'] == 'OK'/*&&$response['docSentiment']['type']!='neutral'*/) { //if the sentiment is not false, the API call was successful.
                    $results[]=array( //add the tweet message in the results




        return $results;

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