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Dive into misinformation detectionfrom unimodal to multimodal and multilingual misinformation detection /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Dive into misinformation detectionby Asif Ekbal, Rina Kumari.
其他題名:	from unimodal to multimodal and multilingual misinformation detection /
作者:	Ekbal, Asif.
其他作者:	Kumari, Rina.
出版者:	Cham :Springer Nature Switzerland :2024.
面頁冊數:	xx, 172 p. :ill. (chiefly col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	MisinformationData processing.
電子資源:	https://doi.org/10.1007/978-3-031-54834-5
ISBN:	9783031548345$q(electronic bk.)

Dive into misinformation detectionfrom unimodal to multimodal and multilingual misinformation detection /
Ekbal, Asif.

Dive into misinformation detectionfrom unimodal to multimodal and multilingual misinformation detection /[electronic resource] :by Asif Ekbal, Rina Kumari. - Cham :Springer Nature Switzerland :2024. - xx, 172 p. :ill. (chiefly col.), digital ;24 cm. - The information retrieval series,v. 302730-6836 ;. - Information retrieval series ;v.37..

1. Introduction -- 2. Recent Advancements in Misinformation Detection -- 3. Novelty and Emotion in Misinformation Detection -- 4. Multitasking for Misinformation Detection -- 5. Multimodality in Misinformation Detection -- 6. Novelty and Emotion in Multimodal Misinformation Detection -- 7. Multilinguality in Misinformation Detection -- 8. Book Summary.

This book delivers a brief introduction to misinformation, and various novel approaches for solving misinformation detection problems. It considers all kinds of false information as fake news or misinformation and uses the terms fake news and misinformation interchangeably, in text, images, audio and video. The primary purpose is to provide a foundation for the problems of misinformation or false content detection including various challenges and approaches to solve them. The book starts with an overall description of misinformation. It briefly introduces the history, various issues or challenges, reasons for creating and spreading misinformation, and its impact on individuals and society. The second chapter discusses prior works on misinformation detection and explores various datasets, recent advancements, and state-of-the-art mechanisms. Chapter three demonstrates that the presence of surprising content in a story draws instant attention and appeals to strong emotional stimuli, and subsequently explores the application of novelty and emotion in the misinformation detection domain. Next, chapter four first introduces multitasking and discusses its advantages, before developing a framework for joint learning of interrelated tasks such as emotion recognition, novelty detection, and misinformation detection. The fifth chapter explores various datasets and mechanisms leveraging multimodal information, and eventually explains the fusion mechanisms of text and image modalities to obtain an efficient multimodal feature that ultimately helps to classify multimedia fake news. Chapter six discusses how novelty and emotion can be helpful in multimodal misinformation detection. It shows that detecting misleading information is difficult without earlier knowledge about that particular news and explores the possible solutions to tackle this problem. Eventually, chapter seven introduces the concept of multilingualism and implements an effective neural model to detect fabricated multilingual information, which overcomes the research and development gap in misinformation detection for regional languages. The final chapter eight briefly summarizes the presented results. This book is mainly written for researchers and graduate students specializing in fake news search and detection, as well as for industry professionals who need to explore various dimensions of misinformation detection regardless of their past knowledge and experience.

ISBN: 9783031548345$q(electronic bk.)

Standard No.: 10.1007/978-3-031-54834-5doiSubjects--Topical Terms:

970318
Misinformation
--Data processing.

LC Class. No.: HM851

Dewey Class. No.: 303.4833

Dive into misinformation detectionfrom unimodal to multimodal and multilingual misinformation detection /
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