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Disinformation in Open Online Media [electronic resource] : 4th Multidisciplinary International Symposium, MISDOOM 2022, Boise, ID, USA, October 11–12, 2022, Proceedings /

Contributor(s): Material type: TextTextSeries: Lecture Notes in Computer Science ; 13545Publisher: Cham : Springer International Publishing : Imprint: Springer, 2022Edition: 1st ed. 2022Description: XIX, 155 p. 51 illus., 44 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783031182532
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 621.39 23
  • 004.6 23
LOC classification:
  • TK7885-7895
  • TK5105.5-5105.9
Online resources:
Contents:
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.
In: Springer Nature eBookSummary: 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 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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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.

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 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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