Commit ac5d538c by Ewan Klein

some renaming of classes, methods

parent cd638344
#!/usr/bin/python # -*- coding: utf-8 -*-
\ No newline at end of file # Natural Language Toolkit: Twitter
#
# Copyright (C) 2001-2015 NLTK Project
# Author: Ewan Klein <ewan@inf.ed.ac.uk>
# URL: <http://nltk.org/>
# For license information, see LICENSE.TXT
"""
NLTK Sentiment Analysis Package
"""
from nltk.sentiment.vader import SentimentIntensityAnalyzer
...@@ -67,10 +67,10 @@ Weblogs and Social Media (ICWSM-14). Ann Arbor, MI, June 2014. ...@@ -67,10 +67,10 @@ Weblogs and Social Media (ICWSM-14). Ann Arbor, MI, June 2014.
... "However, Mr. Carter solemnly argues, his client carried out the kidnapping under orders and in the ''least offensive way possible.''" ... "However, Mr. Carter solemnly argues, his client carried out the kidnapping under orders and in the ''least offensive way possible.''"
... ] ... ]
>>> sentences.extend(tricky_sentences) >>> sentences.extend(tricky_sentences)
>>> sid = SentimentIntensityDetector() >>> sid = SentimentIntensityAnalyzer()
>>> for sentence in sentences: >>> for sentence in sentences:
... print(sentence) ... print(sentence)
... ss = sid.sentiment(sentence) ... ss = sid.polarity_scores(sentence)
... for k in sorted(ss): ... for k in sorted(ss):
... print('{0}: {1}, '.format(k, ss[k]), end='') ... print('{0}: {1}, '.format(k, ss[k]), end='')
... print() ... print()
...@@ -353,7 +353,7 @@ class SentiText(object): ...@@ -353,7 +353,7 @@ class SentiText(object):
class SentimentIntensityDetector(object): class SentimentIntensityAnalyzer(object):
""" """
Give a sentiment intensity score to sentences. Give a sentiment intensity score to sentences.
""" """
...@@ -372,7 +372,7 @@ class SentimentIntensityDetector(object): ...@@ -372,7 +372,7 @@ class SentimentIntensityDetector(object):
lex_dict[w] = float(m) lex_dict[w] = float(m)
return lex_dict return lex_dict
def sentiment(self, text): def polarity_scores(self, text):
""" """
Returns a float for sentiment strength based on the input text. Returns a float for sentiment strength based on the input text.
Positive values are positive valence, negative value are negative Positive values are positive valence, negative value are negative
...@@ -590,8 +590,8 @@ class SentimentIntensityDetector(object): ...@@ -590,8 +590,8 @@ class SentimentIntensityDetector(object):
def demo(): def demo():
text1 = "At least (I think...) it isn't a HORRIBLE :-) book!" text1 = "At least (I think...) it isn't a HORRIBLE :-) book!"
text2 = "Today kinda sux! But I'll get by, lol" text2 = "Today kinda sux! But I'll get by, lol"
sid = SentimentIntensityDetector() sid = SentimentIntensityAnalyzer()
ss1 = sid.sentiment(text1) ss1 = sid.polarity_scores(text1)
print(text1) print(text1)
print(ss1) print(ss1)
...@@ -606,7 +606,7 @@ def demo(): ...@@ -606,7 +606,7 @@ def demo():
""" """
ss2 = sid.sentiment(text2) ss2 = sid.polarity_scores(text2)
print(text2) print(text2)
print(ss2) print(ss2)
......
...@@ -2,13 +2,114 @@ ...@@ -2,13 +2,114 @@
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"source": [
"%env"
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{
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"metadata": {
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"outputs": [],
"source": [
"from nltk.sentiment import SentimentIntensityAnalyzer"
]
},
{
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"metadata": { "metadata": {
"collapsed": true "collapsed": true
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"outputs": [], "outputs": [],
"source": [ "source": [
"from nltk.corpus import sentiwordnet as swn" "from nltk.corpus import tweets"
] ]
}, },
{ {
......
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