Disinformation in Open Online Media: Second Multidisciplinary International Symposium, MISDOOM 2020, Leiden, The Netherlands, October 26-27, 2020, Proceedings

Chapters “Identifying Political Sentiments on YouTube: A Systematic Comparison regarding the Accuracy of Recurrent Neural Network and Machine Learning Models”, “Do Online Trolling Strategies Differ in Political and Interest Forums: Early Results” and “Students Assessing Digital News and Misinformation” are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

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Disinformation in Open Online Media: Second Multidisciplinary International Symposium, MISDOOM 2020, Leiden, The Netherlands, October 26-27, 2020, Proceedings

Chapters “Identifying Political Sentiments on YouTube: A Systematic Comparison regarding the Accuracy of Recurrent Neural Network and Machine Learning Models”, “Do Online Trolling Strategies Differ in Political and Interest Forums: Early Results” and “Students Assessing Digital News and Misinformation” are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

79.99 In Stock
Disinformation in Open Online Media: Second Multidisciplinary International Symposium, MISDOOM 2020, Leiden, The Netherlands, October 26-27, 2020, Proceedings

Disinformation in Open Online Media: Second Multidisciplinary International Symposium, MISDOOM 2020, Leiden, The Netherlands, October 26-27, 2020, Proceedings

Disinformation in Open Online Media: Second Multidisciplinary International Symposium, MISDOOM 2020, Leiden, The Netherlands, October 26-27, 2020, Proceedings

Disinformation in Open Online Media: Second Multidisciplinary International Symposium, MISDOOM 2020, Leiden, The Netherlands, October 26-27, 2020, Proceedings

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Overview

Chapters “Identifying Political Sentiments on YouTube: A Systematic Comparison regarding the Accuracy of Recurrent Neural Network and Machine Learning Models”, “Do Online Trolling Strategies Differ in Political and Interest Forums: Early Results” and “Students Assessing Digital News and Misinformation” are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.


Product Details

ISBN-13: 9783030618414
Publisher: Springer-Verlag New York, LLC
Publication date: 10/20/2020
Series: Lecture Notes in Computer Science , #12259
Sold by: Barnes & Noble
Format: eBook
File size: 27 MB
Note: This product may take a few minutes to download.

Table of Contents

Checkworthiness in Automatic Claim Detection Models: Definitions and Analysis of Datasets.- How Fake News Affect Trust in the Output of a Machine Learning System for News Curation.- A Dip Into a Deep Well: Online Political Advertisements, Valence, and European Electoral Campaigning.- Misinformation from Chinese Web-based Newspapers? Machine Computational Analysis of Metabolic Disease Burden.- Students Assessing Digital News and Misinformation.- Defend Your Enemy. A Qualitative Study on Defending Political Opponents Against Hate Speech Online.- Automatically Identifying Political Ads on Facebook: Towards Understanding of Manipulation via User Targeting.- Identifying Political Sentiments on YouTube: A Systematic Comparison regarding the Accuracy of Recurrent Neural Network and Machine Learning Models.- Abusive Comments in Online Media and How to Fight Them: State of the Domain and a Call to Action.- Fake News Detection on Twitter Using Propagation Structures.- #ArsonEmergency and Australia's "Black Summer": Polarisation and Misinformation on Social Media.- How Identity and Uncertainty Affect Online Social Influence: An Agent-Based Approach.- Do Online Trolling Strategies Differ in Political and Interest Forums: Early Results.- On the Robustness of Rating Aggregators Against Injection Attacks.- FakeYou! - A Gamified Approach for Building and Evaluating Resilience Against Fake News.- Combating Disinformation:  Effects of Timing and Correction Format on Factual Knowledge and Personal Beliefs.- Near Real-Time Detection of Misinformation on Online Social Networks.- Multi-modal Analysis of Misleading Political News.
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