Note that there are some explanatory texts on larger screens.

plurals
  1. POSentiment analysis for Twitter in Python
    text
    copied!<p>I'm looking for an open source implementation, preferably in python, of <strong>Textual Sentiment Analysis</strong> (<a href="http://en.wikipedia.org/wiki/Sentiment_analysis" rel="noreferrer">http://en.wikipedia.org/wiki/Sentiment_analysis</a>). Is anyone familiar with such open source implementation I can use?</p> <p>I'm writing an application that searches twitter for some search term, say "youtube", and counts "happy" tweets vs. "sad" tweets. I'm using Google's appengine, so it's in python. I'd like to be able to classify the returned search results from twitter and I'd like to do that in python. I haven't been able to find such sentiment analyzer so far, specifically not in python. Are you familiar with such open source implementation I can use? Preferably this is already in python, but if not, hopefully I can translate it to python.</p> <p>Note, the texts I'm analyzing are VERY short, they are tweets. So ideally, this classifier is optimized for such short texts.</p> <p>BTW, twitter does support the ":)" and ":(" operators in search, which aim to do just this, but unfortunately, the classification provided by them isn't that great, so I figured I might give this a try myself.</p> <p>Thanks!</p> <p>BTW, an early demo is <a href="http://twitgraph.appspot.com/?show_inputs=1&amp;duration=30&amp;q=youtube+annotations" rel="noreferrer">here</a> and the code I have so far is <a href="http://code.google.com/p/twitgraph/" rel="noreferrer">here</a> and I'd love to opensource it with any interested developer.</p>
 

Querying!

 
Guidance

SQuiL has stopped working due to an internal error.

If you are curious you may find further information in the browser console, which is accessible through the devtools (F12).

Reload