4 ms·

Python NLTK Sentiment Analysis with Text Classification Demo

68 points by llambda 15y ago

jarv 15y ago
The NLTK python lib is a great tool. I've been playing around with this recently and having a lot of fun. More recently I started looking at SCOTUS oral transcripts: http://jarv.org/2012/02/a-text-analysis-of-supreme-court-oral-arguments/ http://jarv.org/2012/02/a-text-analysis-of-supreme-court-ora... The two articles here by the same author are interesting for folks who are interested in more about sentiment analysis http://streamhacker.com/2010/05/10/text-classification-sentiment-analysis-naive-bayes-classifier/ http://streamhacker.com/2010/05/10/text-classification-senti... http://streamhacker.com/2010/06/16/text-classification-sentiment-analysis-eliminate-low-information-features/ http://streamhacker.com/2010/06/16/text-classification-senti...
dotpot 15y ago
https://github.com/dotpot/Custom-String-Parser https://github.com/dotpot/Custom-String-Parser
3pt14159 15y ago
Needs more cowbell. "Wasn't that a fucking great movie?" => 0.7 Negative sentiment.
- mattmcknight 15y ago
  "A better film has never been made. If this film was any better, it would simply cease to exist. Really, nothing about it could be improved. I have no complaints whatsoever about the acting, the script, or the cinematography. I was sad to see it end. I am going to go back tomorrow and watch it again." 1.0 Negative sentiment
  - 3pt14159 15y ago
    WOW! That is unbelievable. Usually things get better with more tokens. What a broken library.
- swasheck 15y ago
  At least it got this one correct. "Mr. Madison, what you've just said is one of the most insanely idiotic things I have ever heard. At no point in your rambling, incoherent response were you even close to anything that could be considered a rational thought. Everyone in this room is now dumber for having listened to it. I award you no points, and may God have mercy on your soul." 0.8 Negative Sentiment.
rhnet 15y ago
I wrote an article on use the NLTK library for gender prediction http://stephenholiday.com/articles/2011/gender-prediction-with-python/ http://stephenholiday.com/articles/2011/gender-prediction-wi... It's quite a versatile library.
radikalus 15y ago
"The movie was great" Neg?
deleted 15y ago
[deleted]
nchuhoai 15y ago
Is there something similar for ruby?
lrvick 15y ago
Worth mentioning: Open source sentiment analysis library based on NLTK: http://github.com/tawlk/synt http://github.com/tawlk/synt (Trains on as much twitter data as you want to learn internet slang) Simple gist to do basic sentiment analysis: https://gist.github.com/1266556 https://gist.github.com/1266556

68 points by llambda 15y ago

jarv 15y ago

The NLTK python lib is a great tool. I've been playing around with this recently and having a lot of fun. More recently I started looking at SCOTUS oral transcripts: http://jarv.org/2012/02/a-text-analysis-of-supreme-court-oral-arguments/ http://jarv.org/2012/02/a-text-analysis-of-supreme-court-ora... The two articles here by the same author are interesting for folks who are interested in more about sentiment analysis http://streamhacker.com/2010/05/10/text-classification-sentiment-analysis-naive-bayes-classifier/ http://streamhacker.com/2010/05/10/text-classification-senti... http://streamhacker.com/2010/06/16/text-classification-sentiment-analysis-eliminate-low-information-features/ http://streamhacker.com/2010/06/16/text-classification-senti...

dotpot 15y ago

https://github.com/dotpot/Custom-String-Parser https://github.com/dotpot/Custom-String-Parser

3pt14159 15y ago

Needs more cowbell. "Wasn't that a fucking great movie?" => 0.7 Negative sentiment.

mattmcknight 15y ago
"A better film has never been made. If this film was any better, it would simply cease to exist. Really, nothing about it could be improved. I have no complaints whatsoever about the acting, the script, or the cinematography. I was sad to see it end. I am going to go back tomorrow and watch it again." 1.0 Negative sentiment
- 3pt14159 15y ago
  WOW! That is unbelievable. Usually things get better with more tokens. What a broken library.
swasheck 15y ago
At least it got this one correct. "Mr. Madison, what you've just said is one of the most insanely idiotic things I have ever heard. At no point in your rambling, incoherent response were you even close to anything that could be considered a rational thought. Everyone in this room is now dumber for having listened to it. I award you no points, and may God have mercy on your soul." 0.8 Negative Sentiment.

rhnet 15y ago

I wrote an article on use the NLTK library for gender prediction http://stephenholiday.com/articles/2011/gender-prediction-with-python/ http://stephenholiday.com/articles/2011/gender-prediction-wi... It's quite a versatile library.

radikalus 15y ago

"The movie was great" Neg?

deleted 15y ago

[deleted]

nchuhoai 15y ago

Is there something similar for ruby?

lrvick 15y ago

Worth mentioning: Open source sentiment analysis library based on NLTK: http://github.com/tawlk/synt http://github.com/tawlk/synt (Trains on as much twitter data as you want to learn internet slang) Simple gist to do basic sentiment analysis: https://gist.github.com/1266556 https://gist.github.com/1266556