Combating Online Hostile Posts in Regional Languages during Emergency Situation

First International Workshop, CONSTRAINT 2021, Collocated with AAAI 2021, Virtual Event, February 8, 2021, Revised Selected Papers
1. Auflage 2021
ISBN: 978-3-030-73695-8
Verlag: Springer International Publishing

Buch, Englisch, Band 1402, 258 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 417 g

Reihe: Communications in Computer and Information Science

This book constitutes selected and revised papers from the First International Workshop on Combating Online Hostile Posts in Regional Languages during Emergency Situation, 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.

Zielgruppe

Research

Autoren/Hrsg.

Chakraborty, Tanmoy

Shu, Kai

Akhtar, Md Shad

Bernard, H. Russell

Liu, Huan

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken

Inhaltsverzeichnis

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.