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    <p>Thank you for the comments thus far. Here is a <a href="http://codepad.org/C359F62N" rel="noreferrer">working solution</a> I prepared with PHP. I'd still be interested in hearing from others a more algorithmic approach to this same solution. </p> <pre><code>&lt;?php // Confusion Matrix Init $tp = 0; $fp = 0; $fn = 0; $tn = 0; $arrFP = array(); $arrFN = array(); // Load All Tweets to string $ch = curl_init(); curl_setopt($ch, CURLOPT_URL, 'http://pastebin.com/raw.php?i=m6pP8ctM'); curl_setopt($ch, CURLOPT_RETURNTRANSFER, 1); $strCorpus = curl_exec($ch); curl_close($ch); // Load Tweets as Array $arrCorpus = explode("\n", $strCorpus); foreach ($arrCorpus as $k =&gt; $v) { // init $blnActualClass = substr($v,0,1); $strTweet = trim(substr($v,2)); // Score Tweet $intScore = score($strTweet); // Build Confusion Matrix and Log False Positives &amp; Negatives for Review if ($intScore &gt; 0) { if ($blnActualClass == 1) { // True Positive $tp++; } else { // False Positive $fp++; $arrFP[] = $strTweet; } } else { if ($blnActualClass == 1) { // False Negative $fn++; $arrFN[] = $strTweet; } else { // True Negative $tn++; } } } // Confusion Matrix and Logging echo " Predicted 1 0 Actual 1 $tp $fp Actual 0 $fn $tn "; if (count($arrFP) &gt; 0) { echo "\n\nFalse Positives\n"; foreach ($arrFP as $strTweet) { echo "$strTweet\n"; } } if (count($arrFN) &gt; 0) { echo "\n\nFalse Negatives\n"; foreach ($arrFN as $strTweet) { echo "$strTweet\n"; } } function LoadDictionaryArray() { $strDictionary = &lt;&lt;&lt;EOD 10|iTunes 10|ios 7 10|ios7 10|iPhone 10|apple inc 10|apple corp 10|apple.com 10|MacBook 10|desk top 10|desktop 1|config 1|facebook 1|snapchat 1|intel 1|investor 1|news 1|labs 1|gadget 1|apple store 1|microsoft 1|android 1|bonds 1|Corp.tax 1|macs -1|pie -1|clientes -1|green apple -1|banana -10|apple pie EOD; $arrDictionary = explode("\n", $strDictionary); foreach ($arrDictionary as $k =&gt; $v) { $arr = explode('|', $v); $arrDictionary[$k] = array('value' =&gt; $arr[0], 'term' =&gt; strtolower(trim($arr[1]))); } return $arrDictionary; } function score($str) { $str = strtolower($str); $intScore = 0; foreach (LoadDictionaryArray() as $arrDictionaryItem) { if (strpos($str,$arrDictionaryItem['term']) !== false) { $intScore += $arrDictionaryItem['value']; } } return $intScore; } ?&gt; </code></pre> <p>The above outputs:</p> <pre><code> Predicted 1 0 Actual 1 31 1 Actual 0 1 17 False Positives 1|Royals apple #ASGame @mlb @ News Corp Building http://instagram.com/p/bBzzgMrrIV/ False Negatives -1|RT @MaxFreixenet: Apple no tiene clientes. Tiene FANS// error.... PAGAS por productos y apps, ergo: ERES CLIENTE. </code></pre>
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    1. POHow can I build a model to distinguish tweets about Apple (Inc.) from tweets about apple (fruit)?
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