Twint is a Python package that provides a very high level abstraction layer to Twitter API and provides the preprocessed results in a pandas dataframe. The system have been built with several key concerns in mind.
- availability of key scores (influence, reach, etc)
- applicability of the data for neural networks
- identification of spam and other bots
- singleline commands for all four important methods:
- streaming API for both keywords and users
- REST API for for keywords
- REST API for user timelines
- Flatfile ingestion from JSON (from Twitter API)
- all methods return identical dataframe
pip install git+https://github.com/mikkokotila/twint.git
search('deep learning',500)
timeline('realdonaldtrump')
stream('cars')
flatfile('some_tweets.json')
| SIGNAL | SOURCE |
|---|---|
| influence_score | Twint |
| reach_score | Twint |
| quality_score | Twint |
| compound | NLTK |
| neu | NLTK |
| neg | NLTK |
| pos | NLTK |
| days_since_creation | |
| user_tweets | |
| user_favourites | |
| user_followers | |
| user_following | |
| user_listed | |
| handle | |
| created_at | |
| default_profile | |
| egg_account | |
| description | |
| location | |
| timezone | |
| expanded_url | |
| url | |
| site_url | |
| retweet_count | |
| text |