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
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for twitter-sentiment-0.0.6.1.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | 459121c731f6fec8432eb2c9a700bf4a4a9887f68df9cf0551fe88b700de7a89 |
|
MD5 | c074c966c80c59df3c7004463d63a199 |
|
BLAKE2b-256 | 097885237887e2a1a18bb05a95af56d7f5bd40548e615b9679087e0fc60726b3 |
Hashes for twitter_sentiment-0.0.6.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 55fbe00b7393cef32c6e38734add8efb009304611279b422ef120376e23f1f8e |
|
MD5 | 92b0f3106786ee46b4433bd19f3d935f |
|
BLAKE2b-256 | 7e22bc9baa620e3ed26ddb7e88610b93ce4acb796e2fb60d48b60f44e8641ed2 |