研究

Authors: 
Guoqiang Lin, School of Systems Science, Beijing Normal University, Beijing 100875, P. R.China
Zengru Di, School of Systems Science, Beijing Normal University, Beijing 100875, P. R.China
Ying Fan, Corresponding author, School of Systems Science, Beijing Normal University, Beijing 100875, P. R.China
Abstract: 

Much empirical evidence shows that when attacked with cascading failures, scale-free or even random networks tend to collapse more extensively when the initially deleted node has higher betweenness. Meanwhile, in networks with strong community structure, high-betweenness nodes tend to be bridge nodes that link different communities, and the removal of such nodes will reduce only the connections among communities, leaving the networks fairly stable.

Authors: 
Hongli Liu, School of Business, East China University of Science and Technology, Shanghai 200237, P. R. China
Yun Xie, School of Business, East China University of Science and Technology, Shanghai 200237, P. R. China
Haibo Hu, Corresponding author, School of Business, East China University of Science and Technology, Shanghai 200237, P. R. China
Zhigao Chen, School of Business, East China University of Science and Technology, Shanghai 200237, P. R. China
Abstract: 

There is a widespread intuitive sense that people prefer participating in spreading the information in which they are interested. The affinity of people with information disseminated can affect the information propagation in social networks. In this paper, we propose an information diffusion model incorporating the mechanism of affinity of people with information which considers the fitness of affinity values of people with affinity threshold of the information.

Authors: 
Qiang Liu, Department of Nuclear Technology Application, China Institute of Atomic Energy, Beijing 102413, P. R. China
Jin-Qing Fang, Corresponding author, Department of Nuclear Technology Application, China Institute of Atomic Energy, Beijing 102413, P. R. China
Yong Li, Department of Nuclear Technology Application, China Institute of Atomic Energy, Beijing 102413, P. R. China
Abstract: 

Network of network (NON) or so-called supernetwork extensively exists in the real world. However, so far the definition of NON is not mutually recognized, relevant theory is rather lacking. In order to reveal certain characteristics of NON, we proposed four kinds of three-layered supernetwork evolution models (TLSEM) based on WS small-world and BA scale-free model, and defined two kinds of layer cross-degrees as new measures of cooperative-competition relationship for different layer nodes.

Authors: 
Yinan Zhao, School of Systems Science, Beijing Normal University, Beijing 100875, P. R. China
Qinghua Chen, Corresponding author, School of Systems Science, Beijing Normal University, Beijing 100875, P. R. China, School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ 85287, USA
Yougui Wang, School of Systems Science, Beijing Normal University, Beijing 100875, P. R. China
Abstract: 

The Lowest Unique Bid Auction (LUBA) booms recently through the Internet. A typical distribution pattern of bid price in this reverse auction has been found and needs to be interpreted. The distribution curve is a decreasing one whose slope has a close relationship with the number of agents participating in the auction. To explain this stylized fact, we develop a model assuming that agents prefer to bid on the price at which the probability of winning is higher.

Authors: 
Fengjing Shao, Corresponding author., College of Information Engineering, Qingdao University, Ningxia Road 308, Qingdao, 266071/Shandong, P. R. China
Yi Sui, College of Information Engineering, Qingdao University, Ningxia Road 308, Qingdao, 266071/Shandong, P. R. China
Abstract: 

Real networks interact with each other by different kinds of topological connections, which are usually demonstrated by linking nodes of different networks. Simple connection, such as one-to-one corresponding, random connection and similar connection are adopted for studying the interacted networks. Practical interrelations established between the two networks are ignored. In this study, a generalized framework of multi-subnet composited complex network that allowed us to investigate interrelations among several subnets is developed.

Online reputation matters for the majority of North American consumers, according to research released by 1&1 Internet Inc., a Web host. The survey, conducted by MaCorr Research, of more than 1,000 North American consumers, found that 80 percent of consumers regularly check the Internet for material about an online retailer, or “e-tailer,” before committing to a purchase. 

In this brief material, we introduce some works on source credibility theory, including trust model, reputation evaluation, rater system and applications.

Most people don't give a lot of consideration to online reputation management until the time comes when they think they need it.
In actuality, you need to institute an online reputation management program before negative mentions of you or your company appear in the SERPs. It's much better to take a proactive approach to owning the real estate on Page 1, as opposed to clawing your way in, after bad news is attached to your brand.

Search engine reputation management (SERM) is reaching the next level. PR firms across the globe are starting to offer elaborate services in corporation with SEO firms. A professional approach doesn't just consist of cleansing the search results once a reputation is already in trouble. Companies need to become aware that all their activities can result in well-ranked online messages that can have a huge effect on the perception of their brand.

What is Search Engine Reputation Management?:
Search engine reputation management (SERM) is the process of monitoring search results related to your name and associated keywords to ensure the results that people see when they search for you using search engines like Google, Yahoo!, and Bing are the ones that you want them to see.

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