posts/context.py

import streamlit as st

title = "Hate Speech Detection in Automatic Content Moderation"
description = "The history and development of hate speech detection as a modeling task"
date = "2022-01-26"
thumbnail = "images/huggingface_logo.png"

def run_article():
  st.markdown("""
  # What is Automatic Content Moderation?

  This is where the history of automatic content moderation (ACM) will go.

  # The Landscape of ACM

  This is where the current platforms and approaches with go.

  # Current Challenges

  This is where the discussion of current challenges, examples from media, and value tensions will go.

  So what does all this mean for conceptualizing this real world problem as a machine learning task? First we'll look at the data, then at the models.
  """)