Social Network Analysis. Группа авторов

      

Table of Contents

      1  Cover

      2  Title Page

      3  Copyright

      4  Preface

      5  1 Overview of Social Network Analysis and Different Graph File Formats 1.1 Introduction—Social Network Analysis 1.2 Important Tools for the Collection and Analysis of Online Network Data 1.3 More on the Python Libraries and Associated Packages 1.4 Execution of SNA in Terms of Real-Time Application: Implementation in Python 1.5 Clarity Toward the Indices Employed in the Social Network Analysis 1.6 Conclusion References

      6  2 Introduction To Python for Social Network Analysis 2.1 Introduction 2.2 SNA and Graph Representation 2.3 Tools To Analyze Network 2.4 Importance of Analysis 2.5 Scope of Python in SNA 2.6 Installation 2.7 Use Case 2.8 Real-Time Product From SNA References

      7  3 Handling Real-World Network Data Sets 3.1 Introduction 3.2 Aspects of the Network 3.3 Graph 3.4 Scale-Free Network 3.5 Network Data Sets 3.6 Conclusion References

      8  4 Cascading Behavior in Networks 4.1 Introduction 4.2 User Behavior 4.3 Cascaded Behavior References

      9  5 Social Network Structure and Data Analysis in Healthcare 5.1 Introduction 5.2 Prognostic Analytics—Healthcare 5.3 Role of Social Media for Healthcare Applications 5.4 Social Media in Advanced Healthcare Support 5.5 Social Media Analytics 5.6 Conventional Strategies in Data Mining Techniques 5.7 Research Gaps in the Current Scenario 5.8 Conclusion and Challenges References

      10  6 Pragmatic Analysis of Social Web Components on Semantic Web Mining 6.1 Introduction 6.2 Background 6.3 Proposed Model 6.4 Building Social Ontology Under the Agriculture Domain 6.5 Validation 6.6 Discussion 6.7 Conclusion and Future Work References

      11  7 Classification of Normal and Anomalous Activities in a Network by Cascading C4.5 Decision Tree and K-Means Clustering Algorithms 7.1 Introduction 7.2 Literature Survey 7.3 Methodology 7.4 Implementation 7.5 Results and Discussion 7.6 Conclusion References

      12  8 Machine Learning Approach To Forecast the Word in Social Media 8.1 Introduction 8.2 Related Works 8.3 Methodology 8.4 Results and Discussion 8.5 Conclusion References

      13  9 Sentiment Analysis-Based Extraction of Real-Time Social Media Information From Twitter Using Natural