Sentiment Analysis Resources: Positive and Negative Words

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You will also find here links towards various lists of positive words and lists of negative words to use in your assignments or projects.

Find below a list of resources for sentiment analysis:

1. Semantria

Semantria applies Text and Sentiment Analysis to tweets, facebook posts, surveys, reviews or enterprise content. See also these links Resources, Excel, Demo

Lexalytics acquired Semantria in 2014 and added their cloud text/sentiment analysis API and Excel plug-in to their product stack.

2. Lexalytics

State-of-the-art technologies to turn unstructured text into useful data. Hundreds of F1000 companies rely on Lexalytics text mining results. Lexalytics Resources

See more information about Sentiment Analysis Explained at Lexalytics.

3. Sentiment Analysis Dictionaries

Check out these Dictionaries!

At the University of Pittsburgh, they have Sentiment Lexicon. It’s a lexicon of about 8,000 words with positive/neutral/negative sentiment. It’s described in more detail in this paper and released under the GPL.

Professor Bing Liu provide an English Lexicon of about 6800 words that you can download, You can also use it for Opinion Mining and Opinion Spam Detection.

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

4. Meaning Cloud

Find more here https://www.meaningcloud.com/

MeaningCloud is the easiest, most powerful and most affordable way to extract the meaning of all kind of unstructured content: social conversations, articles, documents…

5. Wikipedia Resources

6. The Stanford Natural Language Processing Group

Sentiment analysis at The Stanford Natural Language Processing Group with a Live Demo that is loading very hard.

7. Alchemy

Text and sentiment analysis is performed also by Alchemy, which is an IBM company. See the Alchemy Resources and Sentiment Analysis API

AlchemyAPI’s sentiment analysis algorithm looks for words that carry a positive or negative connotation then figures out which person, place or thing they are referring to. It also understands negations (i.e. “this car is good” vs. “this car is not good”) and modifiers (i.e. “this car is good” vs. “this car is really good”). The sentiment analysis API works on documents large and small, including news articles, blog posts, product reviews, comments and Tweets.

8. Online downloadable pdf

Here is an interesting online downloadable pdf about Introduction to Sentiment Analysis

9. SAS

You can also go and check the resources from SAS Sentiment Analysis

10. Python NLTK

Sentiment Analysis with Python NLTK Text Classification Live Demo

11. Downloadable list of positive words or list of negative words:

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Do you know other sentiment analysis resources? Share below.

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