Hate speech is one of the serious issues we see on social media platforms like Facebook and Twitter, mostly from people with political views. I recently shared an article on how to train a machine learning model for the hate speech detection task which you can find here. With its continuation, in this article, I'll walk you through how to build an end-to-end hate speech detection system with Python.

End-to-End Hate Speech Detection with Python

To create an end-to-end application for the task of hate speech detection, you must first learn how to train a machine learning model to detect if there is hate speech in a piece of text. You can easily learn all about hate speech detection with machine learning from here. To deploy this model as an end-to-end application, I will be using the streamlit library in Python which will help us see the predictions of the hate speech detection model in real-time. If you have never used the streamlit library before, you need to install it on your system using the pip command:

  • pip install streamlit

I hope you must have gone through this article for learning about training a hate speech detection model, now here is how you can build an end-to-end application for the task of hate speech detection using Python:

Dataset

As we are using the streamlit library in Python here so you cannot run this application the same way you run your other Python programs. You need to write the command mentioned below in your command prompt or terminal:

  • streamlit run filename.py

Once the above command is executed, it will open a link on your default web browser which will show an end-to-end application where you have to write some text and it will detect if the text contains hate speech, offensive language or not, as shown in the image below.

End-to-End Hate Speech Detection with Python

Summary

So, this is how you can easily build an end-to-end application to detect hate speech using the Python programming language. Hate speech is one of the serious issues we see on social media platforms like Facebook and Twitter, mostly from people with political views. Hope you liked this article on how to build an end-to-end application to detect hate speech with Python. Please feel free to ask your valuable questions in the comments section below.