| Description |
xxii, 295 pages : illustrations ; 25 cm |
| Series |
Intelligent Systems Reference Library ; Volume 65 |
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Intelligent systems reference library ; Volume 65
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| Contents |
Contents note continued: 2.1.Quality Measures -- 2.2.Similarity Measure -- 3.Social Network Datasets -- 3.1.The Zachary Karate Club -- 3.2.The Bottlenose Dolphin network -- 3.3.American College Football Network -- 3.4.Online Social Networks -- 4.Conclusion -- References -- Societal Networks: The Networks of Dynamics of Interpersonal Associations / Sumeet Jain -- 1.Introduction -- 2.Background -- 3.Graphs and Digraphs -- 3.1.Representations of Sigraphs and Sidigraphs -- 3.2.Dynamics of a Social System -- 3.3.Cognitive Balance and Sidigraphs -- 3.4.The Phenomenon of Clustering -- 4.Social Networks -- 5.Societal Networks -- 5.1.The Key Principle -- 5.2.The Origin -- 5.3.Extension to a Formal Model -- 5.4.Structural Equivalence -- 5.5.Reduced Networks -- 5.6.Class Structures -- 5.7.Self-balancing Networks -- 5.8.Long-Term Evaluation -- 6.Some Recent Developments in Dynamic Social Networks -- 6.1.Mining Periodic Behaviour in Dynamic Social Networks -- |
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Contents note continued: 2.3.Limitations of Analysis by Exact Caste Community (CC) and Source of Livelihood (SL) -- 2.4.Formation of Categories of CC and SL -- 3.Brief Historical Background of the Villages -- 3.1.Location and Other Facilities -- 3.2.Settlement Patterns of the Villages -- 4.Social Stratification of the Villages -- 4.1.By Caste Community -- 4.2.Stratification by Source of Livelihood (SL) Categories and Ownership of Land -- 4.3.What Patterns Observed -- 4.4.Inter-relationship of CC and SL Categories in Villages -- 5.Parameters of Life and Living of the Villagers Required for Social Network -- 5.1.Type and Timing of Needs and Urgencies -- 5.2.Availability of Help from Formal Institutions to Satisfy Urgent Needs -- 5.3.How One Decides to Approach Whom for Help or Support -- 5.4.Why Help is Provided -- 5.5.Distance of Spread of Sources of Helps and Assistance -- 6.Findings from Social Network Analysis -- 6.1.From Whom Help was Sought -- |
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Contents note continued: 4.2.Evolution Model in Presence of Restrictions on Node-degree -- 5.Summary -- References -- Machine Learning for Auspicious Social Network Mining / Satchidananda Dehuri -- 1.Introduction -- 2.Representation of Network Data -- 3.Different Aspects of Social Network Analysis -- 3.1.Different Measures of Social Network -- 3.2.Essential Problems and Algorithms -- 4.Statistical Models for Social Network Analysis: Probability and Random Walks -- 5.Groups and Substructures in Social Networks -- 5.1.Bipartite Cores - Identifying Communities -- 6.Machine Learning Based Approaches for Networked Data Mining -- 6.1.Social Analytical Data Preparation with Machine Learning -- 6.2.Machine Learning for Networked Data Mining -- 6.3.Some Highlited Research and Findings Using Machine Learning -- 7.Conclusion -- References -- Testing Community Detection Algorithms: A Closer Look at Datasets / Aly A. Fahmy -- 1.Introduction -- 2.Evaluating Community Detection Methods -- |
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Contents note continued: 4.2.Unstructured Relational Data Sources -- 5.Simulation, Modelling and Computational Terrorism -- 6.Essentials of Social Networks and Centrality Measures -- 7.Case Studies -- 7.1.Case I: The 9/11 Attack on the Trade Towers in New York -- 7.2.Case II: Mapping a Network of Terrorist Organizations in India -- 8.Conclusions -- References -- Privacy and Anonymization in Social Networks / Anirban Mitra -- 1.Introduction -- 1.1.Chapter Structure -- 2.Social Networks -- 3.Privacy in Social Networks -- 3.1.How Users Lose Control of Their Privacy -- 4.Privacy in Published Social Network Data -- 4.1.Social Network Representation -- 4.2.Social Network Analysis -- 4.3.Anonymization -- 4.4.Challenges in Anonymizing Social Networks Data -- 5.Private Information in Published Social Network Data -- 6.Background-Knowledge Attacks -- 6.1.Background Knowledge of Adversaries -- 7.Related Work -- 8.Problem Formulation -- |
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Contents note continued: 6.2.Amount/Quantity and Type of Help Sought -- 6.3.Purpose of Help -- 7.Conclusions -- Appendix A -- Appendix B -- Appendix C -- References -- Evaluating the Propagation Strength of Malicious Metaphor in Social Network: Flow Through Inspiring Influence of Members / Aboul Ella Hassanien -- 1.Introduction -- 2.Fundamental of Social Network: Graph Theory Perspective -- 2.1.Co-Evolution of Social and Affiliation Network -- 3.Exploring Mathematical Treatments -- 3.1.Proposed Algorithm -- 3.2.Experimental Results and Discussion -- 3.3.Comparison with Statistical Model -- 4.Graphical Representation -- 5.Conclusion and Further Scope of Research -- References -- Social Network Analysis: A Methodology for Studying Terrorism / Aparna Basu -- 1.Introduction -- 2.Two Phases in the Development of Social Network Analysis -- 3.Social Network Analysis and Terrorism -- 4.Data Col lection and Data Sources -- 4.1.Structured Data Sources -- |
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Contents note continued: 6.2.Periodic Subgraph Mining Problem -- 6.3.Framework for Analysis of Dynamic Social Networks -- 7.Problems for Further Study -- 8.Conclusion -- References -- Methods of Tracking Online Community in Social Network / G.N. Purohit -- 1.Introduction -- 2.Related Work -- 2.1.Subgroup Identification -- 2.2.Clustering and Partitioning of Subgroups -- 2.3.Similarity -- 2.4.Behavioural Measures of Community -- 3.Existing Methods and Framework for Tracking Communities -- 3.1.Social Cohesion Analysis of Networks (SCAN) -- 3.2.DISSECT (Data-Intensive Socially Similar Evolving Community Tracker) -- 3.3.Framework for DISSECT Method -- 4.Conclusion -- References -- Social Network Analysis Approach for Studying Caste, Class and Social Support in Rural Jharkhand and West Bengal: An Empirical Attempt / Rabindranath Jana -- 1.Introduction -- 2.Methodology -- 2.1.Village Selection for the Study -- 2.2.Data Collection and Level of Analysis -- |
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Contents note continued: 8.Conclusion and Future Work -- Appendix I -- Appendix II -- Appendix III -- References |
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Contents note continued: 9.GASNA: Greedy Algorithm for Social Network Anonymization [24,27] -- 9.1.Clustering Phase -- 9.2.Adjustment Phase -- 9.3.Anonymization Phase -- 10.Empirical Evaluation of GASNA -- 11.Comparison with the Literature -- 12.Conclusion and Future Issues -- 12.1.Varying k Value for k-anonymity According to the Degree of the Nodes Being Considered -- 12.2.Anonymity in Modern Social Networks -- 12.3.Partial Anonymity -- References -- On the Use of Brokerage Approach to Discover Influencing Nodes in Terrorist Networks / Akhilesh Tiwari -- 1.Motivation -- 2.Background -- 3.Terrorist Network Mining -- 4.Calculating Centrality Measures -- 4.1.Degree Centrality -- 4.2.Betweenness Centrality -- 4.3.Closeness Centrality -- 4.4.Eigenvector Centrality -- 5.Brokerage -- 6.Roles Detected by Brokerage Approach -- 6.1.Coordinator -- 6.2.Consultant -- 6.3.Gatekeeper -- 6.4.Representative -- 6.5.Liaison -- 7.Experimental Analysis through Brokerage -- |
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Machine generated contents note: Diffusion of Information in Social Networks / K.P. Subbalakshmi -- 1.Introduction -- 2.Models of Information Diffusion in Social Networks -- 2.1.Mathematical Modeling of Information Diffusion -- 2.2.Influencers in Social Networks -- 2.3.Influencers and Controlling Mis-information Spread in Social Networks -- 2.4.Multiple Sources of Diffusion and the Problem of Information Confusion -- 3.Locating the Source of Diffusion -- 4.Summary -- References -- Structure and Evolution of Online Social Networks / Niloy Ganguly -- 1.Introduction -- 2.Topological Properties of Social Networks -- 2.1.Topological Properties Used to Characterize Large Networks -- 2.2.Topological Properties of OSNs -- 3.Evolution of Social Networks -- 3.1.Evolution Models for Complex Networks -- 3.2.Evolution Models for OSNs -- 4.Evolution of OSNs in Presence of Restrictions on Node-degree -- 4.1.The Restriction in Twitter and Its Effects -- |
| Summary |
With the proliferation of social media and on-line communities in networked world a large gamut of data has been collected and stored in databases. The rate at which such data is stored is growing at a phenomenal rate and pushing the classical methods of data analysis to their limits. This book presents an integrated framework of recent empirical and theoretical research on social network analysis based on a wide range of techniques from various disciplines like data mining, social sciences, mathematics, statistics, physics, network science, machine learning with visualization techniques, and security. The book illustrates the potential of multi-disciplinary techniques in various real life problems and intends to motivate researchers in social network analysis to design more effective tools by integrating swarm intelligence and data mining |
| Bibliography |
Includes bibliographical references |
| Subject |
Computational intelligence.
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Data mining.
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Online social networks.
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Local area networks (Computer networks)
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Social networks -- Computer network resources.
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| Author |
Dehuri, Satchidananda, ditor of compilation
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Panda, Mrutyunjaya, editor of compilation
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Wang, Gi-nam, editor of compilation
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| LC no. |
2014931783 |
| ISBN |
9783319051635 |
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