Title
comeNgo: A Dynamic Model for Social Group Evolution
Abstract
How do social groups, such as Facebook groups and Wechat groups, dynamically evolve over time? How do people join the social groups, uniformly or with burst? What is the pattern of people quitting from groups? Is there a simple universal model to depict the come-and-go patterns of various groups? In this article, we examine temporal evolution patterns of more than 100 thousands social groups with more than 10 million users. We surprisingly find that the evolution patterns of real social groups goes far beyond the classic dynamic models like SI and SIR. For example, we observe both diffusion and non-diffusion mechanism in the group joining process, and power-law decay in group quitting process, rather than exponential decay as expected in SIR model. Therefore, we propose a new model comeNgo, a concise yet flexible dynamic model for group evolution. Our model has the following advantages: (a) Unification power: it generalizes earlier theoretical models and different joining and quitting mechanisms we find from observation. (b) Succinctness and interpretability: it contains only six parameters with clear physical meanings. (c) Accuracy: it can capture various kinds of group evolution patterns preciously, and the goodness of fit increases by 58% over baseline. (d) Usefulness: it can be used in multiple application scenarios, such as forecasting and pattern discovery. Furthermore, our model can provide insights about different evolution patterns of social groups, and we also find that group structure and its evolution has notable relations with temporal patterns of group evolution.
Year
DOI
Venue
2017
10.1145/3059214
TKDD
Keywords
Field
DocType
Group evolution,dynamic model,temporal patterns
Social group,Interpretability,Group structure,Epidemic model,Succinctness,Unification,Computer science,Theoretical computer science,Theoretical models,Artificial intelligence,Goodness of fit,Machine learning
Journal
Volume
Issue
ISSN
11
4
1556-4681
Citations 
PageRank 
References 
0
0.34
8
Authors
7
Name
Order
Citations
PageRank
Tianyang Zhang1574.35
Peng Cui22317110.00
Christos Faloutsos3279724490.38
Christos Faloutsos4279724490.38
hao ye5211.58
Wenwu Zhu64399300.42
Shiqiang Yang72478155.24