A twitter bot that will learn to tweet like a person.
The twitter bot has three modes of operation: train, test, and tweet. Which ever mode is chosen
the code may be run by calling
python main.py $mode $file
where file is the location of a json formatted file of tweet data.
main.py contains sample parameters used to train a twitter bot on tweet data from the Trump Twitter
Archive.
A few steps were taken to clean the data before training. First, all occurrences of & in the data
set are changed to &. Next, various low count characters, primaryly accented characters, are replaced
with appropriate equivalents. Finally, all URLs are removed from tweets. Sample weights obtained from
training are provided in ./weights.
If desired one may change the parameters defining the RNN architecture. The most relevant parameters are
nl and nh which control the number and size of LSTM units used. It should be noted that retraining
is necessary to change run the bot with anything other than the default parameters.
Running the code in test mode will generate five sample tweets. The level of randomness in tweet generation
may be controlled using the parameter passed to the method TwitterBot.genTweet() (0.0 being
completely deterministic and 1.0 sampling the probability distribution at each time step).
To run the twitter bot one must obtain authorization credentials. Once this is done create place them
in ./authorization/keys.auth one string per line in the format:
Consumer Key (API Key)
Consumer Secret (API Secret)
Access Token
Access Token Secret
The application must be given write access for tweets to be automatically posted.
A sample of the twitter bot in action can be found here.