Abstract
Assessing the structural vulnerability of online social networks has been one of the most engaging topics recently, which is quite essential and beneficial to holding the network connectivity and facilitating information flow, but most of the existing vulnerability assessment measures and the corresponding solutions fail to accurately reveal the global damage done to the network. In order to accurately measure the vulnerability of networks, an invulnerability index based on the concept of improved tenacity is proposed in the present study. Compared with existing measurements, the new method does not measure a single property performance, such as giant component size or the number of components after destruction, but pays special attention to the potential equilibrium between the removal cost and the removal effect. Extensive experiments on real-world social networks demonstrate the accuracy and effectiveness of the proposed method. Moreover, compared with results of attacks based on the different centrality indices, we found an individual node’s prominence in a network is inherently related to the structural properties of network. In high centralized networks, the nodes with higher eigenvector are more important than the others in maintaining stability and connectivity. But in low centralized networks, the nodes with higher betweenness are more powerful than the others. In addition, the experimental results indicate that low centralized networks can tolerate high intentional attacks and has a better adaptability to attacks than high centralized networks.
Highlights
With the revolution of the WWW technology, Web 2.0 characterized by social collaborative technologies is emerging and fast-growing
Most experimental studies have shown that the Barabási–Albert (BA) network and other similar heterogeneous networks are very robust to random removals but are very fragile against intentional attacks based on the degree or betweenness [6, 14]
When assessing the vulnerability of a network under intentional attacks, three performance criteria should be concerned in the framework of graph theory [38]: 1) The number of components that are being removed
Summary
With the revolution of the WWW technology, Web 2.0 characterized by social collaborative technologies is emerging and fast-growing. People are increasingly inclined to cultivate their virtual social relations and virtual life on the existing prevalent online social networks [1], such as Facebook, Blogger, Wiki, and Digg. These online social networks can provide favorable platforms for people to exchange opinions or information with one another [2]. Most experimental studies have shown that the Barabási–Albert (BA) network and other similar heterogeneous networks are very robust to random removals but are very fragile against intentional attacks based on the degree or betweenness [6, 14]. Some achievements have been made in the research of some typical network models, but how the dynamical processes, such as resilience to damage or tolerance to attacks, are influenced by the specific topological structure of a network remains unknown
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