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在线社交网络分析(Online Social Network Analysis)电子书

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作       者:方滨兴等

出  版  社:电子工业出版社

出版时间:2017-12-01

字       数:111.7万

所属分类: 科技 > 计算机/网络 > 多媒体/数据通信

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  • 读书简介
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This book focuses on the interaction among three elements of online social networks, i.e. structure, group and information.The structure characteristics and its evolution mechanism, the formation and interaction of group behaviors, and the propagation models and evolution rules of information are discussed in details. This book provides an important theoretical foundation for social network analysis and research on network information dissemination.<br/>【作者】<br/>现任国防科学技术大学计算机学院教授、博士生导师,*基础软件工程中心副主任;国家863计划信息技术领域信息安全主题专家组专家,中国网络空间安全协会副理事长,中央网信办咨询专家组专家,中国计算机学会计算机安全专业委员和数据库专业委员会会常务委员。国家社交网络及其信息服务协同创新中心平台首席科学家,国家973项目"社交网络及信息传播”首席科学家助理。主要研究方向:网络空间安全和大数据分析等,作为课题负责人承担和主持了"863计划”重、国家自然科学基金重等国家重要课题20余项;获国家科技步二等奖3项(排名1,2,3),部委级科技步一等奖7项;发表SCI和EI检索的论文200余篇,出版专著5部,获得30余项发明专利和40余项软件著作权授权。<br/>
目录展开

版权页

前言

Chapter 1 Introduction

1.1 Social Network and Its Development

1.2 Development of Online Social Networks

1.3 Background and Significance of Online Social Network Analysis

1.4 Scientific Questions of Online Social Network Analysis

1.5 Organization of This Book

References

Chapter Social Network Structure Analysis and Modeling

2.1 Introduction

2.2 Examples

2.3 Statistical Characteristics of Social Network

2.4 Social Networking Characteristics Analysis

2.5 Social Network Structure Modeling and Generation

2.6 Summary

References

Chapter 3 Technologies and Approaches for Virtual Community Detection

3.1 Introduction

3.2 Theoretical Basis of Virtual Community Detection Technology

3.3 Static Calculation Detection Algorithms for Virtual Communities

3.4 Dynamic Calculation Detection Algorithms for Virtual Communities

3.5 Summary

References

Chapter 4 Evolution Analysis of Virtual Communities

4.1 Introduction

4.2 Merging of Virtual Communities

4.3 Evolution of Virtual Communities

4.4 Detection of Evolving Virtual Communities

4.5 Summary

References

Chapter 5 Analysis of User Behavior

5.1 Introduction

5.2 Online Social Network User Adoption and Loyalty

5.3 Individual Usage Behavior

5.4 Group Interaction Behavior

5.5 Summary

References

Chapter 6 Social Network Sentiment Analysis

6.1 Introduction

6.2 Sentiment Analysis Techniques

6.3 Social Network Sentiment Analysis Techniques

6.4 Extension and Transformation of Sentiment Analysis Technique

6.5 Summary

References

Chapter 7 Influence Analysis and Its Technologies

7.1 Introduction

7.2 Influence Strength Calculation

7.3 Identification of Influentials

7.4 Summary

References

Chapter 8 Collective Aggregation and the Influence Mechanisms

8.1 Introduction

8.2 Mechanisms Engendering Collective Intelligence

8.3 Mechanisms Engendering Group Polarization

8.4 Summary

References

Chapter 9 Information Retrieval in Social Networks

9.1 Introduction

9.2 Content Search in Social Network

9.3 Content Classification

9.4 Social Network Recommendation

9.5 Summary

References

Chapter 10 The Rules of Information Diffusion in Social Networks

10.1 Introduction

10.2 Influencing Factors Related to Information Diffusion in Social Networks

10.3 Diffusion Model Based on Network Structure

10.4 Diffusion Model Based on the States of Groups

10.5 Diffusion Model Based on Information Characteristics

10.6 Popularity Prediction Method

10.7 Information Source Location

10.8 Summary

References

Chapter 11 Topic Discovery and Evolution

11.1 Introduction

11.2 Models and Algorithms of Topic Discovery

11.3 Models and Algorithms of Topic Evolution

11.4 Summary

Appendix

References

Chapter 12 Algorithms of Influence Maximization

12.1 Introduction

12.2 Basic Concepts and Theory Basis

12.3 Metrics of Influence Maximization

12.4 Classification of Influence Maximization Algorithms

12.5 Greedy Algorithm of Influence Maximization

12.6 Heuristic Algorithms of Influence Maximization

12.7 Extension and Deformation of Influence Maximization

12.8 Summary

References

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