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:
Lexalytics acquired Semantria in 2014 and added their cloud text/sentiment analysis API and Excel plug-in to their product stack.
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…
6. The Stanford Natural Language Processing Group
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
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:
- List of negative words: GitHub negative-words.txt
- List of positive words: Positive Words Research: online + downloadable excel, GitHub positive-words.txt
- SentiWordNet (https://sentiwordnet.isti.cnr.it/) is an excellent publicly available lexicon. Technically, the resource contains Princeton WordNet data marked with polarity scores. (Check its licensing policy before using).
- Hu and Liu’s lexicon: Another option is available at https://www.cs.uic.edu/~liub/FBS/… (look for the section called “Opinion Lexicon”.
- Sentiment lexicon (https://www.cs.pitt.edu/mpqa/) 8221 words scored for polarity (positive or negative), subjectivity. Distinguishes between POS tags.
- General inquirer (https://www.wjh.harvard.edu/~inqu…) has several dictionaries, e.g., a “positive” list with 1’915 words and one ‘negative’ list with 2’291 words
- Affective word list https://www.sci.sdsu.edu/CAL/word…
- Bing Liu and Minquing Hu at the University of Illinois at Chicago have curated a bunch of sentiment datasets. Opinion Mining, Sentiment Analysis, Opinion Extraction
- Not a database but a list of Negative (-ve) words and adjectives list for sentiment analysis
- For Negative words jeffreybreen/twitter-sentiment-analysis-tutorial-201107 and for positive words
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