vaderSentiment

    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