Abstract

Recent years have brought a rise in popularity and useof social media. While this was a hugely positive development,it was accompanied by a proliferation of hate speech, which hasrecently become a major concern. On the one hand, hateful contentcreates an unsafe environment for certain members of society. Onthe other hand, in-person moderation of hate speech causes distressto content moderators.1While initially studied as a text classifi-cation problem, over time, researchers realized that hate speechis multi-faceted and requires analysis of the role of linguistic ex-pression, context, and network structure, while using inspirationfrom psychology and user behavior, among others. With this inmind, in this tutorial, we will provide a holistic view of what theresearch community has explored so far, and what the future holdsfor combating hate speech online.

Tutorial Outline

Mountain Standard Time
  1. Slot-I: (60 mins)
    • Introduction: 20 mins (Dr. Tanmoy)
    • Hate Speech Detection: 30 mins (Dr. Manish)
    • Questions: (10 mins)
  2. Slot-II: (50 mins)
    • Hate Speech Diffusion: 40 mins (Sarah)
    • Questions: (10 mins)
  3. Break: (5 mins)
  4. Slot III: (60 mins)
    • Psychological Analysis of Hate Spreaders: 25 mins (Dr. Amitava)
    • Intervention measures for HS: 25 mins (Sarah)
    • Questions: (15 mins)
  5. Slot IV: (65 mins)
    • Overview of Bias in HS: 25 mins (Pinkesh)
    • Current Developments: 25 mins (Dr. Preslav)
    • Future Scope & Concluding Remarks: 5 mins (Dr. Tanmoy)
    • Questions: (10 mins)

Presenters

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Sarah Masud

Email: sarahm [at] iiitd.ac.in

Homepage: https://sara-02.github.io

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Pinkesh Badjatiya

Email: pbadjati [at] adobe.com

Homepage: https://pinkeshbadjatiya.github.io/

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Dr. Amitava Das

Email: amitava.das2 [at] wipro.com

Homepage: http://www.amitavadas.com

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Dr. Manish gupta

Email: gmanish [at] microsoft.com

Homepage: http://research.microsoft.com/en-us/people/gmanish/

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Dr. Preslav Nakov

Email:pnakov [at] hbku.edu.qa

Homepage: https://www.hbku.edu.qa/en/staff/dr-preslav-nakov

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Dr. Tanmoy Chakraborty

Email: tanmoy [at] iiitd.ac.in

Homepage: http://faculty.iiitd.ac.in/~tanmoy

Lab Page: http://lcs2.iiitd.edu.in/

Tutorial Material

Coming Soon!

Literature Material

  1. Handling Bias in Toxic Speech Detection: A Survey
  2. Hate is the New Infodemic A Topic-aware Modeling of Hate Speech Diffusion on Twitter
  3. Would Your Tweet Invoke Hate on the Fly? Forecasting Hate Intensity of Reply Threads on Twitter
  4. Detecting Harmful Memes and Their Targets
  5. MOMENTA: A Multimodal Framework for Detecting Harmful Memes and Their Targets
  6. Better Prevent than React: Deep Stratified Learning to Predict Hate Intensity of Twitter Reply Chains
  7. Nipping in the Bud: Detection, Diffusion and Mitigation of Hate Speech on Social Media
  8. Anti-Defamation League
  9. A Unified Deep Learning Architecture for Abuse Detection
  10. Leveraging Intra-User and Inter-User Representation Learning for Automated Hate Speech Detection
  11. Characterizing and Detecting Hateful Users on Twitter
  12. Spread of hate speech in online social media
  13. Examining Untempered Social Media Analyzing Cascades of Polarized Conversations (Gab)
  14. Measuring #GamerGate A Tale of Hate, Sexism, and Bullying on Twitter
  15. Generating Counter Narratives against Online Hate Speech Data and Strategies
  16. Analyzing the hate and counter speech accounts on Twitter
  17. CONAN - COunter NArratives through Nichesourcing a Multilingual Dataset of Responses to Fight Online Hate Speech
  18. Fighting Offensive Language on Social Media with Unsupervised Text Style Transfer
  19. Predicting the Type and Target of Offensive Posts in Social Media
  20. Using Transfer-based Language Models to Detect Hateful and Offensive Language Online
  21. Cross-lingual Zero- and Few-shot Hate Speech Detection utilising frozen Transformer Language Models and AXEL
  22. HateBERT Retraining BERT for Abusive Language Detection in English
  23. Hate Speech Detection via GTP-3 Prompts
  24. Exposing the limits of Zero-shot Cross-lingual Hate Speech Detection
  25. Explainable Abusive Language Classification Leveraging User and Network Data
  26. Detecting Propaganda Techniques in Memes
  27. SemEval-2019 Task 6: Identifying and Categorizing Offensive Language in Social Media (OffensEval)
  28. SOLID: A Large-Scale Semi-Supervised Dataset for Offensive Language Identification
  29. Multi-label Categorization of Accounts of Sexism using a Neural Framework
  30. AbuseAnalyzer: Abuse Detection, Severity and Target Prediction for Gab Posts
  31. Deep Learning for Hate Speech Detection in Tweets

Previous Editions

ECML PKDD 2021

Contact

Email sarahm [at] iiitd.ac.in for any query about the tutorial.