Sameer Borate continues on his theme of Twitter-related development (part one is here) with his latest post showing how to do sentiment analysis of Twitter feeds. His "sentiment analysis" analyzes a string to determine if it's generally negative or positive based on the AFINN word dataset.

In the last post we looked into accessing Twitter API v1.1 from PHP. In this post we will see how we can add sentiment analysis for the tweets. Generally speaking, sentiment analysis aims to determine the attitude of a writer with respect to some topic. A basic task in sentiment analysis is classifying the polarity of a given text, whether the expressed opinion in a sentence is positive, negative, or neutral. In this post we will use a simple sentiment analysis library to analyze the sentiment of tweets.

His example uses the viracore/caroline library to do the actual analysis. He shows how to install it via Composer and how to make a sample checker, returning the score and the comparative ranking. With that working, he shows how to integrate it into the Twitter connection originally created in the first post, extracting tweets from his own timeline and returning their scores.