DiscordHateSpeechBot

This is a TF Model that is trained to classify hate speech. It contains a script to run a bot on discord, that will automatically check posts for their hate-score

HowTo

Installation

Make sure you have every needed library installed. You need:

• Python
• pip

With pip you can install:

• matplotlib
• discord py
• tensorflow
• sklearn
• numpy

Training your first model

For that you want to use tensorflow_model_creation.py. These are the arguments:

usage: tensorflow_model_creation.py [-h] [-ds DOWNSAMPLE] [-d] [-c]
                                    [-e EPOCHS] [-r] [-rs RANDOMSTATE]
                                    [-l LOAD] [-ct]

Train tensorflow-network on hate-speech

optional arguments:
  -h, --help            show this help message and exit
  -ds DOWNSAMPLE, --downsample DOWNSAMPLE
                        downsample data, has to be a float between (0, 1) (exclusive)
  -d, --debug           turns debug on
  -c, --cpu             sets runmode to cpu only
  -e EPOCHS, --epochs EPOCHS
                        sets how many epochs the model shall train
  -r, --reprocess       activates the reprocessing of the training data. Has to be run the first time!
  -rs RANDOMSTATE, --randomstate RANDOMSTATE
                        sets a specific random state, used for the random.seed
  -l LOAD, --load LOAD  loads tensorflow model under the given path
  -ct, --continuetraining
                        If a model to load has been passed, this parameter
                        will continue training it. It is advised to supply a
                        new -rs value, to mix up the training data

The script then does everything by itself, no need for you to intervene. The first launch should look like this: python tensorflow_model_creation.py -r

Running the discord bot

First, you need to turn the .env_template file into a .env file and add your bots token. Then, you can run the script with: python discord_hate_speech_bot.py -l pathToYourSavedModel

IMPORTANT:

If you are training your own model, make sure to copy the resulting validation scores from the CLI and paste them into the about section of the code. If you don't change/remove it, the score will be wrong.

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Functions of the bot

Automatic Hate Speech Classification

The bot checks every new message and passed it trough the trained model. If it classifies the text as hate speech, the bot will respond to the message.

Add classification data

Using ?reclassify text|label where label is either 1 or 0, you can help train the model by adding data to a set that will be used to further improve the model.

Check a certain text for its score

By tagging the bot in any message, it respond to it with an embed that contains the classification score

General information

The model is a TensorFlow RNN and is heavily based on this one: https://www.tensorflow.org/tutorials/text/text_classification_rnn

The dataset can be found here: https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge/data

The dataset for training is being reduced from 6 labels to only 1.

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ToDo:

• Make model save a latest_model that can be automatically loaded into the bot
• Make model save validation data so the bot can load it in automatically