《線上社交網路分析(Online Social Network Analysis)》是2017年電子工業出版社出版的圖書、作者是方濱興。
基本介紹
- 中文名：線上社交網路分析(Online Social Network Analysis)
- 作者：方濱興
- 出版社：電子工業出版社
- 出版時間：2017年12月
- 裝幀：平塑
- ISBN：9787121327452
內容簡介,圖書目錄,作者簡介,
內容簡介
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.
圖書目錄
Chapter 1 Introduction 1
1.1 Social Network and Its Development 1
1.1.1 The Origin of Social Network 1
1.1.2 A Glimpse of the Development Procedure of Social Networks From the
Perspective of Sociology 2
1.1.3 A Glimpse of the Development of Social Network From the
Perspective of Anthropology 4
1.2 Development of Online Social Networks 5
1.2.1 Concept of Online Social Networks 5
1.2.2 Features of Online Social Networks 7
1.2.3 Development of Online Social Networks 8
1.2.4 Influences of Online Social Networks on People’s life 9
1.3 Background and Significance of Online Social Network Analysis 11
1.4 Scientific Questions of Online Social Network Analysis 13
1.4.1 Challenges of Online Social Network Analysis 13
1.4.2 Three Scientific Questions and Associated Researches 15
1.5 Organization of This Book 29
References 32
Chapter 2 Social Network Structure Analysis and Modeling 35
2.1 Introduction 35
2.2 Examples 36
2.3 Statistical Characteristics of Social Network 37
2.3.1 Degree Distribution 38
2.3.2 Average Path Length 39
2.3.3 Density 40
2.3.4 Clustering Coefficient 41
2.3.5 Betweenness 42
2.4 Social Networking Characteristics Analysis 43
2.4.1 Small-world Phenomenon 43
2.4.2 Scale-free Characteristic 47
2.4.3 Assortativity 53
2.4.4 Reciprocity 57
2.5 Social Network Structure Modeling and Generation 58
2.5.1 WS Model 59
2.5.2 Extension of WS Model 62
2.5.3 BA Model 63
2.5.4 Extension of BA Model 67
2.5.5 Other Models 70
2.6 Summary 74
References 74
Chapter 3 Technologies and Approaches for Virtual Community Detection 78
3.1 Introduction 78
3.2 Theoretical Basis of Virtual Community Detection Technology 79
3.2.1 The Definition of Virtual Community 79
3.2.2 Development Process of Virtual Community
Detection Algorithms 81
3.2.3 The Accuracy Indexes of Evaluation for Virtual Community
Detection Algorithms 83
3.2.4 The Calculating Complexity of Algorithms for Virtual
Community Detection 88
3.2.5 Typical Data Sets Needed for Testing Virtual Community
Detection Algorithms 89
3.3 Static Calculation Detection Algorithms for Virtual Communities 94
3.3.1 Modularity Optimization Algorithms 95
3.3.2 Multi-objective Optimization Algorithms 98
3.3.3 Algorithms Based on Probability Model 103
3.3.4 Information Coding Algorithms 107
3.4 Dynamic Calculation Detection Algorithms for Virtual Communities 112
3.4.1 Clique Percolation Algorithms 112
3.4.2 Agglomerative Algorithms Based on Similarity 116
3.4.3 Label Propagation Algorithms 120
3.4.4 Local Expansion Optimization Algorithms 125
3.5 Summary 128
References 130
Chapter 4 Evolution Analysis of Virtual Communities 133
4.1 Introduction 133
4.2 Merging of Virtual Communities 134
4.2.1 Period Closure in Merging of Virtual Communities 134
4.2.2 Preference Connection in Merging of Virtual Communities 137
4.2.3 Aging factors in merging of virtual communities 142
4.3 Evolution of Virtual Communities 145
4.3.1 Accumulative Effect in Evolution of Virtual Communities 145
4.3.2 Structural Diversity in Evolution of Virtual Communities 149
4.3.3 Structural Balance in Evolution of Virtual Communities 154
4.4 Detection of Evolving Virtual Communities 156
4.4.1 Detection of Evolving Virtual Community Based on Direct
Similarity Comparison at Adjacent Moments 156
4.4.2 Detection of Evolving Virtual Community Based on Evolution
Clustering Analysis 158
4.4.3 Detection of Evolving Virtual Community Based on Laplacian
Dynamics 159
4.4.4 Detection of Evolving Virtual Community Based on Clique
Percolation Algorithm 161
4.4.5 Detection of Evolving Virtual Community Based on Trend
Analysis on Node Behavior 162
4.5 Summary 163
References 164
Chapter 5 Analysis of User Behavior 167
5.1 Introduction 167
5.2 Online Social Network User Adoption and Loyalty 168
5.2.1 Online Social Network User Adoption 168
5.2.2 Online Social Network User Loyalty 178
5.3 Individual Usage Behavior 189
5.3.1 General Usage Behavior 189
5.3.2 Behavior of Content Generation 195
5.3.3 Behavior of Content Consumption 206
5.4 Group Interaction Behavior 214
5.4.1 Relationship Selection of Group Interaction 214
5.4.2 Content Selection of Group Interaction 220
5.4.3 The Time Law of Group Interaction 222
5.5 Summary 226
References 227
Chapter 6 Social Network Sentiment Analysis 233
6.1 Introduction 233
6.1.1 History of Sentiment Analysis 234
6.1.2 Sentiment Definition and Classification 235
6.1.3 Application of Sentiment Analysis 237
6.2 Sentiment Analysis Techniques 238
6.2.1 Semantic Rule-based Sentiment Analysis 238
6.2.2 Supervised Learning-based Sentiment Analysis 243
6.2.3 Topic Model-based Sentiment Analysis 249
6.3 Social Network Sentiment Analysis Techniques 251
6.3.1 The Sentiment Analysis Technique for Short Text 251
6.3.2 Sentiment Analysis Based on Collective Intelligence 255
6.3.3 Mining Techniques on Spam Opinions in Social Network 258
6.4 Extension and Transformation of Sentiment Analysis Technique 259
6.4.1 Sentiment Summary Technique 259
6.4.2 Sentiment Analysis Technology Based on the Mechanism of
Transfer Learning 261
6.5 Summary 263
References 264
Chapter 7 Introduction Analysis and Its Technologies 267
7.1 Introduction 268
7.2 Influence Strength Calculation 270
7.2.1 Influence Strength Calculation Based on Network Structure 271
7.2.2 Behaviour-based Influence Strength Calculation 272
7.2.3 Topic-based Influence Strength Calculation 274
7.3 Identification of Influentials 277
7.3.1 Individual Influence Calculation Based Network Structure 277
7.3.2 PageRank 282
7.3.3 Individual Influence Calculation Based on Behavior 285
7.3.4 Individual Influence Calculation Based on Topics 289
7.4 Summary 291
References 292
Chapter 8 Collective Aggregation and the Influence Mechanisms 294
8.1 Introduction 295
8.2 Mechanisms Engendering Collective Intelligence 297
8.2.1 Collective Intelligence 297
8.2.2 Self-determination Theory and Collective Intelligence 299
8.2.3 Conditions Engendering Collective Intelligence 301
8.2.4 Factors Influencing Group Intelligence 302
8.2.5 Analytical Models of Collective Intelligence 306
8.2.6 Simulation of Collective Intelligence in Social Networks 313
8.3 Mechanisms Engendering Group Polarization 323
8.3.1 Group Polarization 323
8.3.2 Social Comparison Theory and Group Polarization 325
8.3.3 Conditions Engendering Group Polarization 327
8.3.4 Factors That Influence the Formation of Group Polarization 328
8.3.5 Main Models of Group Polarization Analysis 331
8.3.6 Simulation of Group Polarization in Social Network
Without the Influence of Social Network Structure 342
8.3.7 Simulation of Group Polarization in Social Networks
With the Influence of Social Network Structure 347
8.4 Summary of the Chapter 357
References 359
Chapter 9 Information Retrieval in Social Networks 364
9.1 Introduction 365
9.2 Content Search in Social Network 368
9.2.1 Classical IR and Relevance Feedback Models 369
9.2.2 Query Representation in Microblog Search 379
9.2.3 Document Representation in Microblog Search 385
9.2.4 Microblog Retrieval Models 390
9.3 Content Classification 396
9.3.1 Feature Processing in Short Text Classification 397
9.3.2 Short Text Classification Algorithm 400
9.4 Social Network Recommendation 403
9.4.1 Brief Introduction to Social Recommendation 405
9.4.2 Memory Based Social Recommendation 407
9.4.3 Model Based Social Recommendation 413
9.5 Summary of the Chapter 421
References 422
Chapter 10 Inf
作者簡介
現任國防科學技術大學計算機學院教授、博士生導師，*基礎軟體工程中心副主任；國家863計畫信息技術領域信息安全主題專家組專家，中國網路空間安全協會副理事長，中央網信辦諮詢專家組專家，中國計算機學會計算機安全專業委員和資料庫專業委員會會常務委員。國家社交網路及其信息服務協同創新中心平台首席科學家，國家973項目"社交網路及信息傳播”首席科學家助理。主要研究方向：網路空間安全和大數據分析等，作為課題負責人承擔和主持了"863計畫”重點、國家自然科學基金重點等國家重要課題20餘項；獲國家科技進步二等獎3項（排名1,2,3），部委級科技進步一等獎7項；發表進入SCI和EI檢索的論文200餘篇，出版專著5部，獲得30餘項發明專利和40餘項軟體著作權授權。
