دانلود کتاب Disinformation in Open Online Media: 4th Multidisciplinary International Symposium, MISDOOM 2022, Boise, ID, USA, October 11–12, 2022, Proceedings (Lecture Notes in Computer Science)

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Preface
Organization
Keynote Talks
Hacking Online Virality
From the Infodemic to the Information War: Disinformation Narrative Evolution, Lessons Learned, and Challenges Ahead
The Propagandists’ Playbook: How Search Engines are Manipulated to Threaten Democracy
The Role of Display Advertising in the Disinformation Ecosystem
Contents
User Perception Based Trust Model of Online Sources: A Case Study of Misinformation on COVID-19
1 Introduction
2 Related Work
3 Our Approach: User Perception-Based Trust Model for Websites
3.1 Trust Factors
3.2 Quasi-experiment Design
4 Experimentation and Results
5 Proposed Trust Model
5.1 Trust Score Model
6 Validation and Testing
7 Limitations and Future Work
8 Conclusion
References
Using Artificial Neural Networks to Identify COVID-19 Misinformation
1 Introduction
2 Literature Review
3 Methodology
3.1 Dataset
3.2 Preprocessing and Merging Datasets
3.3 Experiments and Result
4 Discussion
5 Conclusion and Future Work
References
Tracing Political Positioning of Dutch Newspapers
1 Introduction
2 Related Work
2.1 Dimensionality of Political Discourse
2.2 Source Identification
2.3 Text Generation
3 Data
3.1 Data Collection
3.2 Results
4 Coverage Bias
4.1 Log Normalised Mention Frequency
4.2 Relative Normalised Mention Frequency
4.3 Experiments and Results
5 General and Source Specific Political Discourse
5.1 Topic Modelling
5.2 Experiments and Results
5.3 Word Embeddings
5.4 Experiments and Results
6 Discriminating Newspapers by Article Texts
6.1 Experiments and Results
7 Article Generation
7.1 Experiments and Results
8 Discussion
9 Research Limitations and Future Work
10 Conclusion
References
Digital Information Seeking and Sharing Behaviour During the COVID-19 Pandemic in Pakistan
1 Introduction
2 Relevant Literature
3 Methodology
3.1 Pseudo-medicinal Treatments
4 Analysis 1: Search Trends During COVID-19 Pandemic
4.1 Dataset
4.2 Search Interest Regarding Treatment and Prevention of COVID-19
5 Analysis 2: WhatsApp Public Group Data
6 Conclusion
References
Investigating the Validity of Botometer-Based Social Bot Studies
1 Introduction
2 Theoretical and Methodological Limitations of Botometer-Based Social Bot Detection
3 Evaluating Botometer on Samples of Known Humans
4 Evaluating the Performance of Botometer in Real-World Scenarios
4.1 Are Social Bots Following the Twitter Accounts of German Political Parties?
4.2 Are Social Bots Attempting to Spread Vaccine-Critical Information?
5 Related Work
6 Conclusion
References
New Automation for Social Bots: From Trivial Behavior to AI-Powered Communication
1 Introduction
2 Background and Context of Computer-Mediated Communication
3 Three Perspectives
3.1 Evolution of Social Bots
3.2 Multimodal Artificial Content Generation
3.3 Perception of Content in Games and Social Media
4 New Automation
5 Future Challenges Implied by New Automation
5.1 Detection of Automation
5.2 Measurement of Content Quality
5.3 Effects of Automation
5.4 Moderation Interventions and New Platforms
5.5 Ethical Implications
6 Conclusion
References
Moderating the Good, the Bad, and the Hateful: Moderators\' Attitudes Towards ML-based Comment Moderation Support Systems
1 Introduction
2 Theoretical Background
3 Research Approach
4 Findings
4.1 Current Process, System, and Attitudes
4.2 Requirements of Comment Moderation Support Systems
4.3 Acceptance of ML-Based Comment Moderation
5 Concluding Discussion
References
Advancing the Use of Information Compression Distances in Authorship Attribution
1 Introduction
2 Related Works
3 Politicians Dataset
4 Feature Construction: NCD Attribute Vectors
4.1 Disjoint Subsets
4.2 All Data for Training
5 ML Models and Evaluation
5.1 Machine Learning Models
5.2 Evaluation
6 Results
7 Conclusions and Future Work
References
Discourses of Climate Delay in American Reddit Discussions
1 Introduction
2 Related Work
2.1 Discourses of Climate Delay
2.2 Reddit
2.3 Democrats vs. Republicans
2.4 Research Question and Hypotheses
3 Method
3.1 Groups
3.2 Data Acquisition
3.3 Content Analysis
4 Results
4.1 Sample Description
4.2 Descriptive Statistics
4.3 Distribution of Discourses of Climate Delay
5 Discussion
5.1 Hypotheses
5.2 Limitations
5.3 Further Research
6 Conclusion
References
Incremental Machine Learning for Text Classification in Comment Moderation Systems
1 Introduction
2 Theoretical Background
2.1 Comment Moderation and Comment Moderation Systems
2.2 Batch Learning vs. Incremental Learning
2.3 Incremental Learning in Text Classification
3 Research Approach
4 Incremental ML in Comment Moderation Systems
4.1 Design Objectives
4.2 Development
5 Demonstration and Evaluation
6 Concluding Discussion and Future Work
References
Author Index