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Twitter sentiment is a Python library leveraging NLP and the Twitter API to determine the emotion of a tweet

Project description

Python library to Explore Emotions Behind Tweets

twitter-sentiment is a Python library leveraging NLP algorithm and the Twitter API to classify the sentiment of a tweet.

Installation

Installing twitter-sentiment is simple, you just have to use pip. ::

pip install twitter-sentiment

Documentation

Documentation is available at twitter-sentiment.readthedocs.io

twitter-sentiment in a nutshel

twitter-sentiment let you classify a tweet/list of tweets as positive (1) or negative (0). twitter-sentiment then calculate and returns the ration of positive tweets. To classify a tweet, twitter-sentiment levereage TextBlob Naive Byaise NLP library. More information can be find at textblob.readthedocs.io

Continuous Integration

twitter-sentiment uses circleci as a continuous integration tool. Pushing a new git tag to the remote repositiory will trigger circleci workflow and:

  • validate the test in /test/test_twitterSentiment.py
  • check for a match between the VERSION variable in the setup.py file and the git tag version. If all tests pass, the build will be automatically upload to the pypi server

Project details


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