This work constitutes the proceedings of the Second International Workshop on Advances in Social Network and Analysis, held in Las Vegas, NV, USA in August 2008.
Author(s): C. Lee Giles, Marc Smith, John Yen, Haizheng Zhang
Edition: 1st Edition.
Year: 2010
Language: English
Pages: 142
Lecture Notes in Computer Science 5498......Page 1
Advances in Social Network Mining and Analysis: Second International Workshop, SNAKDD 2008 / Las Vegas, NV, USA, August 24-27, 2008 / Revised Selected Papers......Page 2
Preface......Page 4
Organization......Page 7
Table of Contents......Page 9
Introduction......Page 10
Related Work......Page 12
Extracting Label-Independent Features......Page 13
Classifiers......Page 14
Collective Classification......Page 15
Experimental Methodology......Page 16
Effects of Learning Label Dependencies......Page 17
Effects of Label-Independent Features......Page 20
Performance of Specific LI Features......Page 21
Observations about Our Problem Domains and Data Sets......Page 25
Conclusion......Page 26
References......Page 27
Introduction......Page 29
A Measure of Global Influence......Page 30
Influence-Based Modularity......Page 32
Detecting Community Structure......Page 33
A Generalized Model of Influence......Page 34
Zachary's Karate Club......Page 36
College Football......Page 37
Flickr Social Network......Page 38
Related Research......Page 39
References......Page 42
Introduction......Page 45
Our Contributions......Page 46
Clusters......Page 48
Data......Page 49
Stable Statistics......Page 51
Modeling......Page 54
A Locality Based Model......Page 55
Locality Models......Page 57
Experiments and Results......Page 58
$k$-Neighborhood Area Model......Page 60
Conclusion......Page 61
References......Page 62
Introduction......Page 64
Related Work......Page 66
Dynamic Network......Page 67
Aggregate Network......Page 68
Spread Blockers......Page 69
Network Structural Measures......Page 70
Spreading Model......Page 74
Probability of Activation......Page 75
Datasets......Page 76
Results and Discussion......Page 78
Conclusions and Future Work......Page 81
References......Page 82
Introduction......Page 86
Hidden Relational Model......Page 88
Infinite Hidden Relational Model......Page 90
Generative Model......Page 91
Inference with Gibbs Sampling......Page 92
Inference with Variational Approximation......Page 93
Monastery Data......Page 95
Bernard & Killworth Data......Page 97
MovieLens Data......Page 98
Extension: Conditional IHRM......Page 102
Conclusions......Page 103
References......Page 104
Introduction......Page 106
Link Prediction Problem......Page 107
Social Network Model......Page 108
A Feature Taxonomy for Multi-relational Social Networks......Page 109
Group Features......Page 110
Alternative Network Representations......Page 111
Social Media Data Sets......Page 112
Data Description......Page 113
Link-Prediction Results......Page 114
Related Work......Page 118
Discussion......Page 120
References......Page 121
Introduction......Page 123
Minimum Description Length Encodings......Page 126
Sparse Graph Encoding (SGE)......Page 128
Evaluation Criteria......Page 130
Experimental Procedure......Page 131
References......Page 137
Author Index......Page 140
