Cargando…
Lies Kill, Facts Save: Detecting COVID-19 Misinformation in Twitter
Online social networks (ONSs) such as Twitter have grown to be very useful tools for the dissemination of information. However, they have also become a fertile ground for the spread of false information, particularly regarding the ongoing coronavirus disease 2019 (COVID-19) pandemic. Best described...
Formato: | Online Artículo Texto |
---|---|
Lenguaje: | English |
Publicado: |
IEEE
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8043503/ https://www.ncbi.nlm.nih.gov/pubmed/34192115 http://dx.doi.org/10.1109/ACCESS.2020.3019600 |
Ejemplares similares
-
CoAID-DEEP: An Optimized Intelligent Framework for Automated Detecting COVID-19 Misleading Information on Twitter
Publicado: (2021) -
SRIS: Saliency-Based Region Detection and Image Segmentation of COVID-19 Infected Cases
Publicado: (2020) -
An Infoveillance System for Detecting and Tracking Relevant Topics From Italian Tweets During the COVID-19 Event
Publicado: (2020) -
Cross-Cultural Polarity and Emotion Detection Using Sentiment Analysis and Deep Learning on COVID-19 Related Tweets
Publicado: (2020) -
DL-CRC: Deep Learning-Based Chest Radiograph Classification for COVID-19 Detection: A Novel Approach
Publicado: (2020)