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Table of Contents
Intro
Preface
Disease Control Through Social Network Surveillance
Chapter Contributions
Contents
Editors and Contributors
About the Editors
Contributors
Analysis of Public Perceptions Towards the COVID-19 Vaccination Drive: A Case Study of Tweets with Machine Learning Classifiers
1 Introduction
2 A Brief Literature Survey
3 Data Collection, Pre-processing and Methodology
3.1 Raw-Data Acquisition
3.2 Data Pre-processing
3.3 Data Visualization
3.3.1 Geographical Analytics of Tweets
3.3.2 Users with Maximum Tweets
3.3.3 Most Frequent Hashtags
3.3.4 Monthly Statistics of Tweets
3.3.5 Textual Analysis of Tweets
3.3.6 Word and Phrase Associations
4 Experimental Design, Results and Discussions
4.1 Feature Selection
4.2 Platform Employed and Performance Evaluation Parameters
5 Conclusions
References
Spreader-Centric Fake News Mitigation Framework Based on Epidemiology
1 Introduction
2 Related Work
3 Epidemiology Inspired Framework
4 Preliminaries
4.1 Trustingness and Trustworthiness
4.2 Believability
4.3 Community Health Assessment Model
5 Vulnerability Assessment
6 Identification of Infected Population
7 Risk Assessment of Population
8 Infection Control and Prevention
9 Conclusion
References
Understanding How Readers Determine the Legitimacy of Online Medical News Articles in the Era of Fake News
1 Introduction
2 Background and Related Work
2.1 Presentation and Content in True and Fake News Articles
2.2 Detecting Fake News Articles: The Reader's Side
3 Methodology
3.1 Survey 1
3.2 Survey 2
3.3 Survey 3
3.4 Clustering Analysis
4 Results
4.1 Survey 1
4.2 Survey 2
4.3 Survey 3
5 Discussion
6 Conclusion
References
Trends, Politics, Sentiments, and Misinformation: Understanding People's Reactions to COVID-19 During Its Early Stages
1 Introduction
1.1 Contributions
1.2 Organization
2 Related Work
3 Reactions to COVID-19 During its Early Stages: Social Media Analytics
3.1 Dataset and Implementation Environment
3.2 Analysis Results
3.2.1 Number of Posts Related to COVID-19 Over Time
3.2.2 Number of Published News Per Web Site, Per Month
3.2.3 Geographic Distribution of Shared News
3.2.4 Geographic and Temporal Trends in Fake News
3.2.5 Opinions About Public Figures
4 Conclusion
References
Citation Graph Analysis and Alignment Between Citation Adjacency and Themes or Topics of Publications in the Area of Disease Control Through Social Network Surveillance
1 Introduction
2 Literature Review
3 The Citation Graph Methodology
4 Data
4.1 Data Collection
4.2 Derived Networks
5 Discussion of Nodal Attributes of the DCSNS Citation Graph
5.1 Degrees
5.2 Types
5.3 Themes
5.4 Topics
5.5 Relationships Between Nodal Attributes
5.6 Degree and Attribute Assortativities
6 Conclusions
Preface
Disease Control Through Social Network Surveillance
Chapter Contributions
Contents
Editors and Contributors
About the Editors
Contributors
Analysis of Public Perceptions Towards the COVID-19 Vaccination Drive: A Case Study of Tweets with Machine Learning Classifiers
1 Introduction
2 A Brief Literature Survey
3 Data Collection, Pre-processing and Methodology
3.1 Raw-Data Acquisition
3.2 Data Pre-processing
3.3 Data Visualization
3.3.1 Geographical Analytics of Tweets
3.3.2 Users with Maximum Tweets
3.3.3 Most Frequent Hashtags
3.3.4 Monthly Statistics of Tweets
3.3.5 Textual Analysis of Tweets
3.3.6 Word and Phrase Associations
4 Experimental Design, Results and Discussions
4.1 Feature Selection
4.2 Platform Employed and Performance Evaluation Parameters
5 Conclusions
References
Spreader-Centric Fake News Mitigation Framework Based on Epidemiology
1 Introduction
2 Related Work
3 Epidemiology Inspired Framework
4 Preliminaries
4.1 Trustingness and Trustworthiness
4.2 Believability
4.3 Community Health Assessment Model
5 Vulnerability Assessment
6 Identification of Infected Population
7 Risk Assessment of Population
8 Infection Control and Prevention
9 Conclusion
References
Understanding How Readers Determine the Legitimacy of Online Medical News Articles in the Era of Fake News
1 Introduction
2 Background and Related Work
2.1 Presentation and Content in True and Fake News Articles
2.2 Detecting Fake News Articles: The Reader's Side
3 Methodology
3.1 Survey 1
3.2 Survey 2
3.3 Survey 3
3.4 Clustering Analysis
4 Results
4.1 Survey 1
4.2 Survey 2
4.3 Survey 3
5 Discussion
6 Conclusion
References
Trends, Politics, Sentiments, and Misinformation: Understanding People's Reactions to COVID-19 During Its Early Stages
1 Introduction
1.1 Contributions
1.2 Organization
2 Related Work
3 Reactions to COVID-19 During its Early Stages: Social Media Analytics
3.1 Dataset and Implementation Environment
3.2 Analysis Results
3.2.1 Number of Posts Related to COVID-19 Over Time
3.2.2 Number of Published News Per Web Site, Per Month
3.2.3 Geographic Distribution of Shared News
3.2.4 Geographic and Temporal Trends in Fake News
3.2.5 Opinions About Public Figures
4 Conclusion
References
Citation Graph Analysis and Alignment Between Citation Adjacency and Themes or Topics of Publications in the Area of Disease Control Through Social Network Surveillance
1 Introduction
2 Literature Review
3 The Citation Graph Methodology
4 Data
4.1 Data Collection
4.2 Derived Networks
5 Discussion of Nodal Attributes of the DCSNS Citation Graph
5.1 Degrees
5.2 Types
5.3 Themes
5.4 Topics
5.5 Relationships Between Nodal Attributes
5.6 Degree and Attribute Assortativities
6 Conclusions