Metadata-Version: 2.1
Name: gersent
Version: 0.0.6
Summary: Simple german sentiment
Home-page: https://github.com/comnGuy/gersent
Author: Bernhard Preisler
Author-email: bpblub@gmail.com
License: UNKNOWN
Description: # GerSent
        
        GerSent is a project that tries to make a relativ good sentiment of a german sentence. Our first approach will be simple techniques like wordlist or interpration to assess the given sentence.
        
        ## Getting Started
        
        First you have to install our package.
        `pip install gersent`
        
        Now you are able to run a simple sentiment analysis over a german sentence.
        
        ```python
        from gersent import GerSent
        
        ger_senti = GerSent()
        
        print(ger_senti.sentiment('Ich bin ein guter Satz.')
        ```
        
        ## Configurations
        
        ## Examples
        
        Positiv
        ```python
        # Die Ã„pfel schmecken gut.
        {'negative': 0.0, 'positive': 0.3716, 'composite': 0.3716}
        
        # Die Ã„pfel schmecken gut!
        {'negative': 0.0, 'positive': 0.39018, 'composite': 0.39018}
        
        # Die Ã„pfel schmecken gut!!!
        {'negative': 0.0, 'positive': 0.42733999999999994, 'composite': 0.42733999999999994}
        
        # Die Ã„pfel schmecken sehr gut!
        {'negative': 0.0, 'positive': 0.39018, 'composite': 0.39018}
        ```
        
        Negativ
        ```python
        # Die Ã„pfel schmecken nicht gut.
        {'negative': -0.0, 'positive': -0.3716, 'composite': -0.3716}
        ```
        # References
        
        Wordlists
        
        R. Remus, U. Quasthoff & G. Heyer: SentiWS - a Publicly Available German-language Resource for Sentiment Analysis.
        In: Proceedings of the 7th International Language Ressources and Evaluation (LREC'10), 2010
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
