Hate speech: Detection, Mitigation and Beyond @WSDM

Hate Alert

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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 negative 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 deeply engraved into our society and is often linked with offline violence. Social media platforms rely on human moderators to identify hate speech and take necessary action. However, with the increase in online hate speech, these platforms are turning toward automated hate speech detection and mitigation systems. This shift brings several challenges to the plate, and hence, is an important avenue to explore for the computation social science community. In this tutorial, we present an exposition of hate speech detection and mitigation in three steps. First, we describe the current state of research in the hate speech domain, focusing on different hate speech detection and mitigation systems that have developed over time. Next, we highlight the challenges that these systems might carry like bias and the lack of transparency. The final section concretizes the path ahead, providing clear guidelines for the community working in hate speech and related domains. We also outline the open challenges and research directions for interested researchers.

Date

Mar 27, 2023 8:30 AM — 11:30 AM

Event

WSDM Tutorials

Important updates

Slides can be found here
Video of the tutorial can be found here!!

Contributions and achievements

Our papers are accepted in top conferences/journals like PNAS, NeurIPS, LREC, AAAI, IJCAI, WWW, ECML-PKDD, CSCW, ICWSM, HyperText and WebSci. Link to the papers here
We have open sourced our codes and datasets under a single github organisation - hate-alert for the future research in this domain
We have stored different transformers models in huggingface.co. Link to hatealert organisation
Dataset from our recent accepted paper in AAAI - “Hatexplain:A Benchmark Dataset for Explainable Hate Speech Detection” is also stored in the huggingface datsets forum
We also participate in several hate speech shared tasks, winning many of them - hatealert@URDU_SOC, hatealert@DLTEACL, hateminers@AMI, hatemonitors@HASOC and coming under 1% in hatealert@Hatememe detection by Facebook AI.
Notion page containing hate speech papers.

Tutorial Outline

Outline of the Tutorial

Introduction (25 mins)
Analysis (40 mins)
1. Prevalence of hate speech.
2. Targets of hate speech.
3. Effects of hate speech.
4. Effect of offline events.
Detection (40 mins)
1. Summary of different datasets.
  1. Unimodal.
  2. Multimodal.
2. Earlier detection models.
3. Current detection models .
4. Multimodal and multilingual hate speech.
5. Challenge.
  1. Evaluation.
  2. Explainability.
  3. Bias.
Mitigation (40 mins).
1. Counterspeech campaigns.
2. Banning and suspending users.
3. Counterspeech detection.
4. Counterspeech generation.
5. Effect of counter speech.
Demo (15 mins).
Future Challenge (10 mins).

About the Organizers

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. 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. 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.

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.