KavelCortex / twee2vec

Using tweepy to crawl specific user's twitter, then use word2vec to vectorize the user.

twee2vec

using tweepy to crawl specific user's twitter, then use word2vec to vectorize the user.

USAGE

Account

First fill in the blank in utils/account.py, which contains Twitter API token information from your Twitter Dev Account.

consumer_key = 'YOUR_CONSUMER_KEY'
consumer_secret = 'YOUR_CONSUMER_SECRET'
access_token = 'YOUR_ACCESS_TOKEN'
access_secret = 'YOUR_ACCESS_SECRET'

After that, feel free to use any of the functions from utils 😉

Word2Vec

In order to use word2vec function, you need to first download pre-trained models from here:

'crawl-300d-2M-subword' by Facebook https://fasttext.cc/docs/en/english-vectors.html

'GoogleNews-vectors-negative300' by Google https://code.google.com/archive/p/word2vec/

then place the models in ./model, you are good to go.

MILESTONES

• Stream Twitter by keywords
• Extract specified user's twitter
• Implement Word2Vec
• Vectorize user's twitter
• Characterize user based on the extracted vector
• Compare user similarity based on vectors