Microblog Social Network Analysis Based on Network Group Behavior

2013 ◽  
Vol 798-799 ◽  
pp. 435-438
Author(s):  
Lin Wang ◽  
Yang Zhao ◽  
She Hong Liang ◽  
Kan Shi
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Group Behavior ◽  
Scientific Basis ◽  
Network Centrality ◽  
Relationship Matrix ◽  
Close Attention ◽  
Mixed Network ◽  
Exchange Data

This paper has searched the six key influential network group incidents in 2011 in China through SINA Microblog platform, screen the most active Microblog users who pay close attention to the incidents, their Microblog followers are above 50,000 , finally collects 30 Microblog user information by the way of snowballing, form 30*30 “follow – be followed ” Microblog netizens relationship matrix. Specific to this asymmetric matrix, the authors use UCINET social network analysis software and visual software NETDRAW, analyze Microblog network structure, network centrality based on network group incidents, and comprehensively describe the laws to release and acquire group incidents under the mixed network environment of Microblog, combined with the massive Microblog exchange data, to analyze the non-rational behavior of the netizens, so as to provide a scientific basis for setting out the appropriate guiding strategy and interventions.

scholarly journals Terrorist Group Behavior Prediction by Wavelet Transform-Based Pattern Recognition

2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Ze Li ◽  
Duoyong Sun ◽  
Bo Li ◽  
Zhanfeng Li ◽  
Aobo Li
Keyword(s):  
Pattern Recognition ◽  
Social Network ◽  
Wavelet Transform ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Group Behavior ◽  
Terrorist Group ◽  
Attack Behavior ◽  
Terrorist Groups ◽  
Terrorist Acts

Predicting terrorist attacks by group networks is an important but difficult issue in intelligence and security informatics. Effective prediction of the behavior not only facilitates the understanding of the dynamics of organizational behaviors but also supports homeland security’s missions in prevention, preparedness, and response to terrorist acts. There are certain dynamic characteristics of terrorist groups, such as periodic features and correlations between the behavior and the network. In this paper, we propose a comprehensive framework that combines social network analysis, wavelet transform, and the pattern recognition approach to investigate the dynamics and eventually predict the attack behavior of terrorist group. Our ideas rely on social network analysis to model the terrorist group and extract relevant features for group behaviors. Next, based on wavelet transform, the group networks (features) are predicted and mutually checked from two aspects. Finally, based on the predicted network, the behavior of the group is recognized based on the correlation between the network and behavior. The Al-Qaeda data are investigated with the proposed framework to show the strength of our approaches. The results show that the proposed framework is highly accurate and is of practical value in predicting the behavior of terrorist groups.

Influence of Opinion Leaders on Purchase Intention Using Social Network Analysis

2018 ◽  
Vol 10 (1) ◽  
pp. 1-16
Author(s):  
Yi-Fen Chen ◽  
Chia-Wen Tsai ◽  
Yu-Fu Ann
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Purchase Intention ◽  
Mobile Apps ◽  
Peer Group ◽  
Group Structure ◽  
Perceived Value ◽  
Opinion Leader ◽  
Network Centrality

This article examines social network centralities to identify peer group's opinion leader with the aim of determining whether an opinion leader and perceived value influence purchase intention in the field of paid mobile apps. Social network analysis (SNA) and regression analysis are applied to examine the hypotheses within the theoretical framework. The experiment involved a peer group of college students with total of 46 subjects. Using SPSS to analyze the influences of perceived value and the group's opinion leader on purchase intention, the results showed that consumer purchase intention is positively influenced by both the perceived value of paid mobile apps and positive advices given by opinion leader. In addition, an analysis using Ucinet 6 to examine consulting network centrality, friendship network centrality, and information centrality of every member of the group revealed that based on group structure, the group member having the highest centrality has the group's potential to be the opinion leader.

The Overlap of Collaboration and Planning Networks: A Post-Harvey Study

2021 ◽  
pp. 0739456X2199589
Author(s):  
Bryce Hannibal ◽  
Sierra Woodruff ◽  
Matthew Malecha
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Hazard Mitigation ◽  
Network Centrality

This paper uses social network analysis to assess the overlap of organizations involved in hazard mitigation and planning networks in Houston, TX. We compare measures of network centrality and density to highlight unique characteristics across two networks and discuss implications of connectivity within each network. Results suggest that central actors occupy important structural locations within both networks. These overlapping organizations may be highly influential in both planning and hazard mitigation efforts. Finally, we discuss aspects of connectivity in these networks and discuss how the networks can be used to become more equitable and holistic in planning and hazard mitigation efforts.

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