Sentiment Analysis Dictionaries

Question

I was wondering if anybody knew where I could obtain dictionaries of positive and negative words. I\'m looking into sentiment analysis and this is a crucial part of it.

Answer 1

You can use vader sentiment lexicon

from nltk.sentiment.vader import SentimentIntensityAnalyzer

sentence='APPle is good for health'
sid = SentimentIntensityAnalyzer()
ss = sid.polarity_scores(sentence)  
print(ss)

it will give you the polarity of sentence.

output:

 {'compound': 0.4404, 'neu': 0.58, 'pos': 0.42, 'neg': 0.0}

Answer 2

This paper from 2002 describes an algorithm for deriving such a dictionary from text samples automatically, using only two words as a seed set.

Answer 3

AFINN you can find here and also create it dynamically. Like whenever unknown +ve word comes add it with +1. Like banana is new +ve word and appearing twice then it will become +2.

As much articles and data you craws your dictionary would become stronger!

Answer 4

Sentiwords gives 155,000 words (and their polarity, that is, a score between -1 and 1 for very negative through to very positive). The lexicon is discussed here

Answer 5

Arriving a bit late I'll just note that dictionaries have a limited contribution for sentiment analysis. Some sentiment bearing sentences do not contain any "sentiment" word - e.g. "read the book" which could be positive in a book review while negative in a movie review. Similarly, the sentiment word "unpredictable" could be positive in the context of a thriller but negative when describing the breaks system of the Toyota.

and there are many more...

Answer 6

Sentiment Analysis (Opinion Mining) lexicons

• MPQA Subjectivity Lexicon
• Bing Liu and Minqing Hu Sentiment Lexicon
• SentiWordNet (Included in NLTK)
• VADER Sentiment Lexicon
• SenticNet
• LIWC (not free)
• Harvard Inquirer
• ANEW

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Sources:

• Keenformatics - Sentiment Analysis lexicons and datasets (my blog)
• Hutto, C. J., and Eric Gilbert. "Vader: A parsimonious rule-based model for sentiment analysis of social media text." Eighth International AAAI Conference on Weblogs and Social Media. 2014.
• Sentiment Symposium Tutorial by Christopher Potts
• Personal experience