SMAC: Subgraph Matching and Centrality in Huge Social Networks

2013 ◽  
Author(s):  
Noseong Park ◽  
Michael Ovelgonne ◽  
V.S. Subrahmanian
Keyword(s):  
Social Networks ◽  
Subgraph Matching

scholarly journals A Comparative Study of Subgraph Matching Isomorphic Methods in Social Networks

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 66621-66631 ◽  
Author(s):  
TingHuai Ma ◽  
Siyang Yu ◽  
Jie Cao ◽  
Yuan Tian ◽  
Abdullah Al-Dhelaan ◽  
...  
Keyword(s):  
Social Networks ◽  
Comparative Study ◽  
Subgraph Matching

scholarly journals A user interest community evolution model based on subgraph matching for social networking in mobile edge computing environments

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Liang Jiang ◽  
Lu Liu ◽  
Jingjing Yao ◽  
Leilei Shi
Keyword(s):  
Social Networks ◽  
Social Networking ◽  
Fundamental Problem ◽  
Rapid Development ◽  
Edge Computing ◽  
Mobile Edge Computing ◽  
User Interest ◽  
Subgraph Matching ◽  
Model Based ◽  
Community Evolution

AbstractWith the rapid development of mobile edge computing, mobile social networks are gradually infiltrating into our daily lives, in which the communities are an important part of social networks. Internet of People such as online social networks is the next frontier for the Internet of Things. The combination of social networking and mobile edge computing has an important application value and is the development trend of future networks. However, how to detect evolutionary communities accurately and efficiently in dynamic heterogeneous social networks remains a fundamental problem. In this paper, a novel User Interest Community Evolution (UICE) model based on subgraph matching is proposed for accurately detecting the corresponding communities in the evolution of the user interest community. The community evolutionary events can be quickly captured including forming, dissolving, evolving and so on with the introduction of core subgraph. A variant of subgraph matching, called Subgraph Matching with Dynamic Weight (SMDW), is proposed to solve the problem of updating the core subgraph due to the change of core user’s interest when tracking evolutionary communities. Finally, the experiments based on the real datasets have been designed to evaluate the performance of the proposed model by comparing it with the state-of-art methods in this area and complete data processing through the local edge computing layer. The experimental results demonstrate that the UICE model presented in this paper has achieved better accuracy, higher efficiency and better scalability against existing methods.

Privacy-Preserving Subgraph Matching Scheme with Authentication in Social Networks

2020 ◽  
pp. 1-1
Author(s):  
Xiangjian Zuo ◽  
Lixiang Li ◽  
Haipeng Peng ◽  
Shoushan Luo ◽  
Yixian Yang
Keyword(s):  
Social Networks ◽  
Privacy Preserving ◽  
Subgraph Matching

Efficient Techniques for Graph Searching and Biological Network Mining

2011 ◽  
pp. 89-111
Author(s):  
Alfredo Ferro ◽  
Rosalba Giugno ◽  
Alfredo Pulvirenti ◽  
Dennis Shasha
Keyword(s):  
Social Networks ◽  
Computational Complexity ◽  
Biological Network ◽  
Graph Searching ◽  
Search Methods ◽  
Large Graphs ◽  
Network Mining ◽  
Subgraph Matching ◽  
Key Concepts ◽  
Np Complete

From biochemical applications to social networks, graphs represent data. Comparing graphs or searching for motifs on such data often reveals interesting and useful patterns. Most of the problems on graphs are known to be NP-complete. Because of the computational complexity of subgraph matching, reducing the candidate graphs or restricting the space in which to search for motifs is critical to achieving efficiency. Therefore, to optimize and engineer isomorphism algorithms, design indexing and suitable search methods for large graphs are the main directions investigated in the graph searching area. This chapter focuses on the key concepts underlying the existing algorithms. First it reviews the most known used algorithms to compare two algorithms and then it describes the algorithms to search on large graphs making emphasis on their application on biological area.

Multilayer Social Networks

2016 ◽  
Author(s):  
Mark E. Dickison ◽  
Matteo Magnani ◽  
Luca Rossi
Keyword(s):  
Social Networks ◽  
Multilayer Social Networks

Hostility and Perceptions of Support in Ambiguous Social Interactions

2006 ◽  
Vol 27 (2) ◽  
pp. 108-115 ◽  
Author(s):  
Ana-Maria Vranceanu ◽  
Linda C. Gallo ◽  
Laura M. Bogart
Keyword(s):  
Social Support ◽  
Social Networks ◽  
Information Processing ◽  
Social Interactions ◽  
Social Information Processing ◽  
Perceived Social Support ◽  
Social Information ◽  
Inverse Association ◽  
Processing Bias ◽  
Information Processing Bias

The present study investigated whether a social information processing bias contributes to the inverse association between trait hostility and perceived social support. A sample of 104 undergraduates (50 men) completed a measure of hostility and rated videotaped interactions in which a speaker disclosed a problem while a listener reacted ambiguously. Results showed that hostile persons rated listeners as less friendly and socially supportive across six conversations, although the nature of the hostility effect varied by sex, target rated, and manner in which support was assessed. Hostility and target interactively impacted ratings of support and affiliation only for men. At least in part, a social information processing bias could contribute to hostile persons' perceptions of their social networks.

Sign in / Sign up

Export Citation Format

Share Document