| TÃtulo : |
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 |
| Tipo de documento: |
documento electrónico |
| Autores: |
Chakraborty, Tanmoy, ; Shu, Kai, ; Bernard, H. Russell, ; Liu, Huan, ; Akhtar, Md Shad, |
| Mención de edición: |
1 ed. |
| Editorial: |
[s.l.] : Springer |
| Fecha de publicación: |
2021 |
| Número de páginas: |
XI, 258 p. 19 ilustraciones |
| ISBN/ISSN/DL: |
978-3-030-73696-5 |
| Nota general: |
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. |
| Palabras clave: |
Gestión de base de datos Inteligencia artificial Ciencias sociales Software de la aplicacion Sistema de administración de base de datos Aplicación informática en ciencias sociales y del comportamiento Aplicaciones informáticas y de sistemas de información |
| Ãndice Dewey: |
005.7 Datos en sistemas de computadoras |
| Resumen: |
Este libro constituye artÃculos seleccionados y revisados ​​del Primer Taller Internacional sobre la lucha contra publicaciones hostiles en lÃnea en idiomas regionales durante situaciones de emergencia, CONSTRAINT 2021, ubicado junto con AAAI 2021, celebrado como evento virtual, en febrero de 2021. El 14 completo Los artÃculos y 9 artÃculos breves presentados fueron revisados ​​minuciosamente y seleccionados entre 62 presentaciones calificadas. Los artÃculos presentan enfoques interdisciplinarios sobre análisis de redes sociales multilingües y formas no convencionales de combatir publicaciones hostiles en lÃnea. |
| Nota de contenido: |
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. |
| En lÃnea: |
https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] |
| Link: |
https://biblioteca.umanizales.edu.co/ils/opac_css/index.php?lvl=notice_display&i |
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 [documento electrónico] / Chakraborty, Tanmoy, ; Shu, Kai, ; Bernard, H. Russell, ; Liu, Huan, ; Akhtar, Md Shad, . - 1 ed. . - [s.l.] : Springer, 2021 . - XI, 258 p. 19 ilustraciones. ISBN : 978-3-030-73696-5 Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
| Palabras clave: |
Gestión de base de datos Inteligencia artificial Ciencias sociales Software de la aplicacion Sistema de administración de base de datos Aplicación informática en ciencias sociales y del comportamiento Aplicaciones informáticas y de sistemas de información |
| Ãndice Dewey: |
005.7 Datos en sistemas de computadoras |
| Resumen: |
Este libro constituye artÃculos seleccionados y revisados ​​del Primer Taller Internacional sobre la lucha contra publicaciones hostiles en lÃnea en idiomas regionales durante situaciones de emergencia, CONSTRAINT 2021, ubicado junto con AAAI 2021, celebrado como evento virtual, en febrero de 2021. El 14 completo Los artÃculos y 9 artÃculos breves presentados fueron revisados ​​minuciosamente y seleccionados entre 62 presentaciones calificadas. Los artÃculos presentan enfoques interdisciplinarios sobre análisis de redes sociales multilingües y formas no convencionales de combatir publicaciones hostiles en lÃnea. |
| Nota de contenido: |
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. |
| En lÃnea: |
https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] |
| Link: |
https://biblioteca.umanizales.edu.co/ils/opac_css/index.php?lvl=notice_display&i |
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