Containment of RumorsunderLimitCost Budget in Social Network

With widely usingof computer and mobile devices available, people share information more frequently on the online social network (OSN) than before, so information spread faster and wider, especially misinformation andrumors. Rumors on the OSN often make E-commerce companiessuffermuch financial losses.Once there is a rumor, the companies always try to control the rumor propagating so that they suffer the least loss by using a certain budget. In this paper,an effective method on information blocking maximization with cost budget (CIBM) is proposed to solve rumor containment problem with cost budget in e-commerce environment. First, CIBM is proved as NP-hardproblem withthe characteristic of sub-modular and monotone.Then a community dividing algorithm based community structure is presented to optimize containment of the rumors. To verify our proposed method, a lot of experiments are conducted on real dataset and random generated datasets. And the experiment results show that our algorithm has advantage over traditional methods

Applications of Temporal Graph Metrics to Real-World Networks

Real world networks exhibit rich temporal information: friends are added and removed over time in online social networks; the seasons dictate the predator-prey relationship in food webs; and the propagation of a virus depends on the network of human contacts throughout the day. Recent studies have demonstrated that static network analysis is perhaps unsuitable in the study of real world network since static paths ignore time order, which, in turn, results in static shortest paths overestimating available links and underestimating their true corresponding lengths. Temporal extensions to centrality and efficiency metrics based on temporal shortest paths have also been proposed. Firstly, we analyse the roles of key individuals of a corporate network ranked according to temporal centrality within the context of a bankruptcy scandal; secondly, we present how such temporal metrics can be used to study the robustness of temporal networks in presence of random errors and intelligent attacks; thirdly, we study containment schemes for mobile phone malware which can spread via short range radio, similar to biological viruses; finally, we study how the temporal network structure of human interactions can be exploited to effectively immunise human populations. Through these applications we demonstrate that temporal metrics provide a more accurate and effective analysis of real-world networks compared to their static counterparts.Comment: 25 page

Organizational Design for Spill Containment in Deepwater Drilling Operations in the Gulf of Mexico: Assessment of the Marine Well Containment Company (MWCC)

The Deepwater Horizon oil spill in the Gulf of Mexico in April 2010 led to the deaths of 11 workers, a six-month moratorium on deepwater drilling in the Gulf, and nearly three months of massive engineering and logistics efforts to stop the spill. The series of failures before the well was finally capped and the spill contained revealed an inability to deal effectively with a well in deepwater and ultradeepwater. Ensuring that containment capabilities are adequate for drilling operations at these depths is therefore a salient challenge for government and industry. In this paper we assess the Marine Well Containment Company (MWCC), a consortium aimed at designing and building a system capable of containing future deepwater spills in the Gulf. We also consider alternatives for long-term readiness for deepwater spill containment. We focus on the roles of liability and regulation as determinants of readiness and the adequacy of incentives for technological innovation in oil spill containment technology to keep pace with advances in deepwater drilling capability. Liability and regulation can significantly influence the strength of these incentives. In addition, we discuss appropriate governance structure as a major determinant of the effectiveness of MWCC.oil spill, containment, industry R&D, liability, regulation, governance, innovation