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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 1st ed. 2021 [Mīkstie vāki]

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  • Formāts: Paperback / softback, 258 pages, height x width: 235x155 mm, weight: 454 g, 19 Illustrations, black and white; XI, 258 p. 19 illus., 1 Paperback / softback
  • Sērija : Communications in Computer and Information Science 1402
  • Izdošanas datums: 09-Apr-2021
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 3030736954
  • ISBN-13: 9783030736958
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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 1st ed. 2021Palielināt
  • Formāts: Paperback / softback, 258 pages, height x width: 235x155 mm, weight: 454 g, 19 Illustrations, black and white; XI, 258 p. 19 illus., 1 Paperback / softback
  • Sērija : Communications in Computer and Information Science 1402
  • Izdošanas datums: 09-Apr-2021
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 3030736954
  • ISBN-13: 9783030736958
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9783030736958.html
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.
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.