LEADER 06821nam 2200505 450 001 996495571103316 005 20231110224350.0 010 $a3-031-18253-7 035 $a(MiAaPQ)EBC7102394 035 $a(Au-PeEL)EBL7102394 035 $a(CKB)24950540800041 035 $a(PPN)26585556X 035 $a(EXLCZ)9924950540800041 100 $a20230227d2022 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aDisinformation in open online media $e4th multidisciplinary international symposium, MISDOOM 2022, Boise, ID, USA, October 11-12, 2022, proceedings /$fedited by Francesca Spezzano [and four others] 210 1$aCham, Switzerland :$cSpringer,$d[2022] 210 4$d©2022 215 $a1 online resource (172 pages) 225 1 $aLecture Notes in Computer Science ;$vv.13545 311 08$aPrint version: Spezzano, Francesca Disinformation in Open Online Media Cham : Springer International Publishing AG,c2022 9783031182525 320 $aIncludes bibliographical references and index. 327 $aIntro -- 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. 327 $aDigital 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. 327 $a5 Concluding Discussion -- References -- Advancing the Use of Information Compression Distances in Authorship Attribution -- 1 Introduction -- 2 Related Works -- 3 Politicians Dataset -- 4 Feature Construction: NCD Attribute Vectors -- 4.1 Disjoint Subsets -- 4.2 All Data for Training -- 5 ML Models and Evaluation -- 5.1 Machine Learning Models -- 5.2 Evaluation -- 6 Results -- 7 Conclusions and Future Work -- References -- Discourses of Climate Delay in American Reddit Discussions -- 1 Introduction -- 2 Related Work -- 2.1 Discourses of Climate Delay -- 2.2 Reddit -- 2.3 Democrats vs. Republicans -- 2.4 Research Question and Hypotheses -- 3 Method -- 3.1 Groups -- 3.2 Data Acquisition -- 3.3 Content Analysis -- 4 Results -- 4.1 Sample Description -- 4.2 Descriptive Statistics -- 4.3 Distribution of Discourses of Climate Delay -- 5 Discussion -- 5.1 Hypotheses -- 5.2 Limitations -- 5.3 Further Research -- 6 Conclusion -- References -- Incremental Machine Learning for Text Classification in Comment Moderation Systems -- 1 Introduction -- 2 Theoretical Background -- 2.1 Comment Moderation and Comment Moderation Systems -- 2.2 Batch Learning vs. Incremental Learning -- 2.3 Incremental Learning in Text Classification -- 3 Research Approach -- 4 Incremental ML in Comment Moderation Systems -- 4.1 Design Objectives -- 4.2 Development -- 5 Demonstration and Evaluation -- 6 Concluding Discussion and Future Work -- References -- Author Index. 410 0$aLecture Notes in Computer Science 606 $aDigital media 606 $aCommon fallacies 606 $aDigital media$vCongresses 615 0$aDigital media. 615 0$aCommon fallacies. 615 0$aDigital media 676 $a001.96 702 $aSpezzano$b Francesca 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996495571103316 996 $aDisinformation in Open Online Media$92950616 997 $aUNISA