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Dive into misinformation detection = from unimodal to multimodal and multilingual misinformation detection /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Dive into misinformation detection/ by Asif Ekbal, Rina Kumari.
Reminder of title:	from unimodal to multimodal and multilingual misinformation detection /
Author:	Ekbal, Asif.
other author:	Kumari, Rina.
Published:	Cham :Springer Nature Switzerland : : 2024.,
Description:	xx, 172 p. :ill. (chiefly col.), digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer Nature eBook
Subject:	Misinformation - Data processing. -
Online resource:	https://doi.org/10.1007/978-3-031-54834-5
ISBN:	9783031548345

Dive into misinformation detection = from 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. 30..

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

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

3715978
Misinformation
--Data processing.

LC Class. No.: HM851

Dewey Class. No.: 303.4833

Dive into misinformation detection = from unimodal to multimodal and multilingual misinformation detection /
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245 1 0 $a Dive into misinformation detection $h [electronic resource] : $b from unimodal to multimodal and multilingual misinformation detection / $c by Asif Ekbal, Rina Kumari.
260 $a Cham : $b Springer Nature Switzerland : $b Imprint: Springer, $c 2024.
300 $a xx, 172 p. : $b ill. (chiefly col.), digital ; $c 24 cm.
490 1 $a The information retrieval series, $x 2730-6836 ; $v v. 30
505 0 $a 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.
520 $a 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.
650 0 $a Misinformation $x Data processing. $3 3715978
650 0 $a Fake news $x Data processing. $3 3717117
650 1 4 $a Information Storage and Retrieval. $3 761906
650 2 4 $a Artificial Intelligence. $3 769149
650 2 4 $a Natural Language Processing (NLP) $3 3381674
650 2 4 $a Computer Crime. $3 3382518
700 1 $a Kumari, Rina. $3 3717115
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Information retrieval series ; $v v. 30. $3 3717116
856 4 0 $u https://doi.org/10.1007/978-3-031-54834-5
950 $a Computer Science (SpringerNature-11645)