Hate speech: Detection, Mitigation and Beyond

Image credit: Unsplash

Abstract

Social media sites such as Twitter and Facebook have connected billions of people and given the opportunity to the users to share their ideas and opinions instantly. That being said, there are several ill consequences as well such as online harassment, trolling, cyber-bullying, fake news, and hate speech. Out of these, hate speech presents a unique challenge as it is deep engraved into our society and is often linked with offline violence. Social media platforms rely on local moderators to identify hate speech and take necessary action, but with a prolific increase in such content over the social media many are turning toward automated hate speech detection and mitigation systems. This shift brings several challenges on the plate, and hence, is an important avenue to explore for the computation social science community.

Date
Jun 7, 2021 12:00 AM — Jun 10, 2021 12:00 AM

👉 Bookmark the page to stay updated !!!

Table of contents

To be added soon

Tutorial Outline

In this translation style tutorial, we present an exposition of hate speech detection and mitigation in three steps. The following section presents a detailed plan for the tutorial:-

  1. Analysis of hate content
    1. How hate speech is inflicting different platforms?
    2. Existing datasets
  2. Hate speech detection
    1. Text-based systems
    2. User-based systems
  3. Mitigation of hate speech
    1. Banning and suspending users
    2. Counter speech detection
  4. Challenges ahead
    1. Explainability and bias
    2. Multimodal and multilingual challenges.
    3. Nuances of hate speech datasets.
  5. Road to the future
    1. Branches and extensions of hate speech.
    2. Connections to offline violence.
    3. Guidelines for building better dataset.
    4. Adapting to newer events and platforms.

Organizers detail

Punyajoy Saha is a PhD scholar at the Department of Computer Science and Engineering, Indian Institute of Technology, Kharagpur (India). His research interests lies in the nexus of social computing and natural language processing. He is currently involved in developing mitigation algorithms for hate speech in social media. His works are published at major conferences like The Web Conference, AAAI, ECML-PKDD and ICWSM.More about him can be found here.

Binny Mathew is a PhD scholar at the Department of Computer Science and Engineering, Indian Institute of Technology, Kharagpur (India). His research interest lies in computational social science and natural language processing. He is currently interested in solving issues surrounding hate speech in online social media and providing solutions to counter them. His works are published in leading conferences such as The Web Conference, ICWSM, ECML-PKDD, and WebSci. More about him can be found here.

Mithun Das is a PhD scholar at the Department of Computer Science and Engineering, Indian Institute of Technology, Kharagpur (India). His research interests lie in computational social science and natural language processing. More about him can be found here.

Pawan Goyal is an Associate Professor at the Department of Computer Science and Engineering, Indian Institute of Technology, Kharagpur (India). His research interest lies in natural language processing and text mining. More about him can be found here.

Kiran Garimella is the first IDSS postdoctoral fellow to receive a Hammer Fellowship, pioneers research into the spread of rumors and misinformation on closed platforms such as WhatsApp, a popular encrypted messaging service with millions of users worldwide. Kiran aims to develop technical solutions to such problems by building tools that can collect and analyze massive social media datasets. More about him can be found here.

Animesh Mukherjee is an Associate Professor at the Department of Computer Science and Engineering, Indian Institute of Technology, Kharagpur (India). His research interest lies in natural language processing, information retrieval and AI and ethics. More about him can be found here.