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Record Nr. |
UNINA9910616387803321 |
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Titolo |
Disinformation in Open Online Media : 4th Multidisciplinary International Symposium, MISDOOM 2022, Boise, ID, USA, October 11–12, 2022, Proceedings / / edited by Francesca Spezzano, Adriana Amaral, Davide Ceolin, Lisa Fazio, Edoardo Serra |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
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ISBN |
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Edizione |
[1st ed. 2022.] |
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Descrizione fisica |
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1 online resource (172 pages) |
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Collana |
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Lecture Notes in Computer Science, , 1611-3349 ; ; 13545 |
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Disciplina |
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Soggetti |
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Computer engineering |
Computer networks |
Computer Engineering and Networks |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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User Perception Based Trust Model of Online Sources: A Case Study of Misinformation on COVID-19 -- Using Artificial Neural Networks to Identify COVID-19 Misinformation -- Tracing Political Positioning of Dutch Newspapers -- Digital Information Seeking and Sharing Behavior During the COVID-19 Pandemic in Pakistan -- Investigating the Validity of Botometer-based Social Bot Studies -- New Automation for Social Bots: From Trivial Behavior to AI-Powered Communication -- Moderating the Good, the Bad, and the Hateful: Moderators’ Attitudes towards ML-based Comment Moderation Support Systems -- Advancing the use of information compression distances in authorship attribution -- Discourses of Climate Delay in American Reddit Discussions -- Incremental Machine Learning for Text Classification in Comment Moderation Systems. |
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Sommario/riassunto |
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This book constitutes the refereed proceedings of the 4th Multidisciplinary International Symposium on Disinformation in Open Online Media, MISDOOM 2022, held in October 2022. The 7 full papers |
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and 3 short papers were carefully reviewed and selected from 17 full/short paper submissions. The papers focus on health and climate change misinformation, social bots and comment moderation, information seeking and diffusion, misinformation detection, and user perception-based trust models. |
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