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JNLE-NLPOCO 2021 : Journal of Natural Language Engineering - Special Issue on NLP Approaches to Offensive Content Online | |||||||||||||||
Link: https://sites.google.com/view/nle-offensive-content-online | |||||||||||||||
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Call For Papers | |||||||||||||||
Call for Papers
Journal of Natural Language Engineering - Special Issue on NLP Approaches to Offensive Content Online URL: https://sites.google.com/view/nle-offensive-content-online Motivated by the interest of the NLP community in the problem of offensive content online, we are editing a special issue of the Cambridge University Press Journal Natural Language Engineering on NLP Approaches to Offensive Content Online to be published in 2022. We welcome papers dealing with one or more of the following topics: - NLP models for detecting impolite and offensive content online (e.g. hate speech, cyberbulling, aggression, etc.); - Application of NLP tools to analyze social media content and other large data sets for offensive language detection; - NLP models for cross-lingual offensive language identification; - Computational models for multi-modal abuse detection; - Development of corpora and annotation guidelines and taxonomies for offensive language identification; - Human-Computer Interaction (HCI) for abusive language detection systems. More information is available on the special issue website. Important Dates - Deadline for Submissions: August 31, 2021 - First decision: November 30, 2021 - Revised Version Submissions: January 20, 2022 - Final Decisions: April 30, 2022 Guest Editors Isabelle Augenstein - University of Copenhagen, Denmark and CheckStep Ltd, UK Siddharth Krishnan - University of North Carolina at Charlotte, USA Joshua Melton - University of North Carolina at Charlotte, USA Preslav Nakov - Qatar Computing Research Institute, Qatar Marcos Zampieri - Rochester Institute of Technology, USA |
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