Special issue on infodemics
- Authors
- Camacho, David; Gómez-Romero, Juan; Jung, Jason J.
- Issue Date
- Mar-2024
- Publisher
- Springer Science and Business Media Deutschland GmbH
- Keywords
- Deep learning; Disinformation; Fake news; Infodemics; Machine learning; Natural language processing; Real-world applications; Social network analysis
- Citation
- Journal of Ambient Intelligence and Humanized Computing
- Journal Title
- Journal of Ambient Intelligence and Humanized Computing
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/73129
- DOI
- 10.1007/s12652-024-04784-0
- ISSN
- 1868-5137
1868-5145
- Abstract
- In this editorial, we explore the urgent challenges created by the rise of infodemics —a term used to describe the epidemic spread of fake news, misinformation, and disinformation through social networks initially associated with the COVID-19 pandemic. This issue has drawn significant attention from various academic fields, including computer science, artificial intelligence, mathematics, physics, biology, sociology, and psychology, among others. This special issue is dedicated to advancing infodemics research across various academic domains. The selected papers include relevant contributions advancing the state of the art in the area, ranging from network analysis for identifying influential nodes and communities in networks to language processing for text classification and filtering relevant messages within extensive corpora. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.
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Collections - College of Software > School of Computer Science and Engineering > 1. Journal Articles
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