Overview

This book constitutes selected and revised papers from the First International Workshop on Combating On​line Ho​st​ile Posts in ​Regional Languages dur​ing Emerge​ncy Si​tuation, CONSTRAINT 2021, Collocated with AAAI 2021, held as virtual event, in February 2021.  The 14 full papers and 9 short papers presented were thoroughly reviewed and selected from 62 qualified submissions. The papers present  interdisciplinary approaches on multilingual social media analytics and non-conventional ways of combating online hostile posts.

Full Product Details

Author:   Tanmoy Chakraborty ,  Kai Shu ,  H. Russell Bernard ,  Huan Liu
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
Edition:   1st ed. 2021
Volume:   1402
Weight:   0.454kg
ISBN:  

9783030736958

ISBN 10:   3030736954
Pages:   258
Publication Date:   09 April 2021
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Identifying Offensive Content in Social Media Posts.- Identification and Classification of Textual Aggression in Social Media: Resource Creation and Evaluation.- Fighting an Infodemic: COVID-19 Fake News Dataset.- Revealing the Blackmarket Retweet Game: A Hybrid Approach.- Overview of CONSTRAINT 2021 Shared Tasks: Detecting English COVID-19 Fake News and Hindi Hostile Posts.- LaDiff ULMFiT: A Layer Differentiated training approach for ULMFiT.- Extracting latent information from datasets in The CONSTRAINT-2020 shared task on the hostile post detection.- Fake news and hostile posts detection using an ensemble learning model.- Transformer-based Language Model Fine-tuning Methods for COVID-19 Fake News Detection.- Tackling the infodemic : Analysis using Transformer based models.- Exploring Text-transformers in AAAI 2021 Shared Task: COVID-19 Fake News Detection in English.- g2tmn at Constraint@AAAI2021: Exploiting CT-BERT and Ensembling Learning for COVID-19 Fake News Detection.- Model Generalization on COVID-19 Fake News Detection.- ECOL: Early Detection of COVID Lies Using Content, Prior Knowledge and Source Information.- Evaluating Deep Learning Approaches for Covid19 Fake News Detection.- A Heuristic-driven Ensemble Framework for COVID-19 Fake News Detection.- Identification of COVID-19 related Fake News via Neural Stacking.- Fake News Detection System using XLNet model with Topic Distributions: CONSTRAINT@AAAI2021 Shared Task.- Coarse and Fine-Grained Hostility Detection in Hindi Posts using Fine Tuned Multilingual Embeddings.- Hostility Detection in Hindi leveraging Pre-Trained Language Models.- Stacked embeddings and multiple fine-tuned XLM-RoBERTa models for Enhanced hostility identification.- Task Adaptive Pretraining of Transformers for Hostility Detection.- Divide and Conquer: An Ensemble Approach for Hostile Post Detection in Hindi.

Reviews

Author Information

Tab Content 6

Author Website:  

Countries Available

All regions