vaderSentiment


NamevaderSentiment JSON
Version 3.3.2 PyPI version JSON
download
home_pagehttps://github.com/cjhutto/vaderSentiment
SummaryVADER Sentiment Analysis. VADER (Valence Aware Dictionary and sEntiment Reasoner) is a lexicon and rule-based sentiment analysis tool that is specifically attuned to sentiments expressed in social media, and works well on texts from other domains.
upload_time2020-05-22 15:06:32
maintainer
docs_urlNone
authorC.J. Hutto
requires_python
licenseMIT License
keywords
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
                    

        VADER (Valence Aware Dictionary and sEntiment Reasoner) is a lexicon and rule-based sentiment analysis tool that is *specifically attuned to sentiments expressed in social media*. It is fully open-sourced under the `[MIT License] <http://choosealicense.com/>`_ (we sincerely appreciate all attributions and readily accept most contributions, but please don't hold us liable).

        

        **Citation Information**

        

        If you use either the dataset or any of the VADER sentiment analysis tools (VADER sentiment lexicon or Python code for rule-based sentiment analysis engine) in your research, please cite the above paper. For example:  

        

          **Hutto, C.J. & Gilbert, E.E. (2014). VADER: A Parsimonious Rule-based Model for Sentiment Analysis of Social Media Text. Eighth International Conference on Weblogs and Social Media (ICWSM-14). Ann Arbor, MI, June 2014.** 

        

        
        * Code examples are provided on the `[VADER GitHub Repo] <https://github.com/cjhutto/vaderSentiment>`_

        * Details about the scoring are provided on the `[VADER GitHub Repo] <https://github.com/cjhutto/vaderSentiment>`_

        * VADER has been ported to Java, JavaScript, PHP, Scala, C#, Rust, and Go (see details and links to these on the `[VADER GitHub Repo] <https://github.com/cjhutto/vaderSentiment>`_

        
        

        
Keywords: vader,sentiment,analysis,opinion,mining,nlp,text,data,text analysis,opinion analysis,sentiment analysis,text mining,twitter sentiment,opinion mining,social media,twitter,social,media
Platform: any
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.5
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Text Processing :: Linguistic
Classifier: Topic :: Text Processing :: General
Description-Content-Type: text/x-rst

            

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