Concentric Characterization and Classification of Complex Network Nodes: Theory and Application to Institutional Collaboration

Differently from theoretical scale-free networks, most of real networks present multi-scale behavior with nodes structured in different types of functional groups and communities. While the majority of approaches for classification of nodes in a complex network has relied on local measurements of the topology/connectivity around each node, valuable information about node functionality can be obtained by Concentric (or Hierarchical) Measurements. In this paper we explore the possibility of using a set of Concentric Measurements and agglomerative clustering methods in order to obtain a set of functional groups of nodes. Concentric clustering coefficient and convergence ratio are chosen as segregation parameters for the analysis of a institutional collaboration network including various known communities (departments of the University of S\~ao Paulo). A dendogram is obtained and the results are analyzed and discussed. Among the interesting obtained findings, we emphasize the scale-free nature of the obtained network, as well as the identification of different patterns of authorship emerging from different areas (e.g. human and exact sciences). Another interesting result concerns the relatively uniform distribution of hubs along the concentric levels, contrariwise to the non-uniform pattern found in theoretical scale free networks such as the BA model.Comment: 15 pages, 13 figure

Identifying the starting point of a spreading process in complex networks

When dealing with the dissemination of epidemics, one important question that can be asked is the location where the contamination began. In this paper, we analyze three spreading schemes and propose and validate an effective methodology for the identification of the source nodes. The method is based on the calculation of the centrality of the nodes on the sampled network, expressed here by degree, betweenness, closeness and eigenvector centrality. We show that the source node tends to have the highest measurement values. The potential of the methodology is illustrated with respect to three theoretical complex network models as well as a real-world network, the email network of the University Rovira i Virgili

Quantifying the interdisciplinarity of scientific journals and fields

There is an overall perception of increased interdisciplinarity in science, but this is difficult to confirm quantitatively owing to the lack of adequate methods to evaluate subjective phenomena. This is no different from the difficulties in establishing quantitative relationships in human and social sciences. In this paper we quantified the interdisciplinarity of scientific journals and science fields by using an entropy measurement based on the diversity of the subject categories of journals citing a specific journal. The methodology consisted in building citation networks using the Journal Citation Reports database, in which the nodes were journals and edges were established based on citations among journals. The overall network for the 11-year period (1999-2009) studied was small-world and scale free with regard to the in-strength. Upon visualizing the network topology an overall structure of the various science fields could be inferred, especially their interconnections. We confirmed quantitatively that science fields are becoming increasingly interdisciplinary, with the degree of interdisplinarity (i.e. entropy) correlating strongly with the in-strength of journals and with the impact factor.Comment: 23 pages, 6 figure

Topological measures for the analysis of wireless sensor networks

Concepts such as energy dependence, random deployment, dynamic topological update, self-organization, varying large number of nodes are among many factors that make WSNs a type of complex system. However, when analyzing WSNs properties using complex network tools, classical topological measures must be considered with care as they might not be applicable in their original form. In this work, we focus on the topological measures frequently used in the related field of Internet topological analysis. We illustrate their applicability to the WSNs domain through simulation experiments. In the cases when the classic metrics turn out to be incompatible, we propose some alternative measures and discuss them based on the WSNs characteristics.Comment: 3rd International Conference on Ambient Systems (ANT), Networks and Technologies, Niagara Falls : Canada (2012

Characteristics of Real Futures Trading Networks

Futures trading is the core of futures business, and it is considered as one of the typical complex systems. To investigate the complexity of futures trading, we employ the analytical method of complex networks. First, we use real trading records from the Shanghai Futures Exchange to construct futures trading networks, in which nodes are trading participants, and two nodes have a common edge if the two corresponding investors appear simultaneously in at least one trading record as a purchaser and a seller respectively. Then, we conduct a comprehensive statistical analysis on the constructed futures trading networks. Empirical results show that the futures trading networks exhibit features such as scale-free behavior with interesting odd-even-degree divergence in low-degree regions, small-world effect, hierarchical organization, power-law betweenness distribution, disassortative mixing, and shrinkage of both the average path length and the diameter as network size increases. To the best of our knowledge, this is the first work that uses real data to study futures trading networks, and we argue that the research results can shed light on the nature of real futures business.Comment: 18 pages, 9 figures. Final version published in Physica

Fast Community Identification by Hierarchical Growth

A new method for community identification is proposed which is founded on the analysis of successive neighborhoods, reached through hierarchical growth from a starting vertex, and on the definition of communities as a subgraph whose number of inner connections is larger than outer connections. In order to determine the precision and speed of the method, it is compared with one of the most popular community identification approaches, namely Girvan and Newman's algorithm. Although the hierarchical growth method is not as precise as Girvan and Newman's method, it is potentially faster than most community finding algorithms.Comment: 6 pages, 5 figure

Community Structure Characterization

This entry discusses the problem of describing some communities identified in a complex network of interest, in a way allowing to interpret them. We suppose the community structure has already been detected through one of the many methods proposed in the literature. The question is then to know how to extract valuable information from this first result, in order to allow human interpretation. This requires subsequent processing, which we describe in the rest of this entry

Promiscuity and the Evolution of Sexual Transmitted Diseases

We study the relation between different social behaviors and the onset of epidemics in a model for the dynamics of sexual transmitted diseases. The model considers the society as a system of individual sexuated agents that can be organized in couples and interact with each other. The different social behaviors are incorporated assigning what we call a promiscuity value to each individual agent. The individual promiscuity is taken from a distributions and represents the daily probability of going out to look for a sexual partner, abandoning its eventual mate. In terms of this parameter we find a threshold for the epidemic which is much lower than the classical fully mixed model prediction, i.e. $R_0$ (basic reproductive number) $= 1$. Different forms for the distribution of the population promiscuity are considered showing that the threshold is weakly sensitive to them. We study the homosexual and the heterosexual case as well.Comment: 6 pages, 4 figure

What are the Best Hierarchical Descriptors for Complex Networks?

This work reviews several hierarchical measurements of the topology of complex networks and then applies feature selection concepts and methods in order to quantify the relative importance of each measurement with respect to the discrimination between four representative theoretical network models, namely Erd\"{o}s-R\'enyi, Barab\'asi-Albert, Watts-Strogatz as well as a geographical type of network. The obtained results confirmed that the four models can be well-separated by using a combination of measurements. In addition, the relative contribution of each considered feature for the overall discrimination of the models was quantified in terms of the respective weights in the canonical projection into two dimensions, with the traditional clustering coefficient, hierarchical clustering coefficient and neighborhood clustering coefficient resulting particularly effective. Interestingly, the average shortest path length and hierarchical node degrees contributed little for the separation of the four network models.Comment: 9 pages, 4 figure

Local food systems: concepts, impacts, and issues

Consumer demand for food that is locally produced,marketed, and consumed is generating increased interest in local food throughout the United States. As interest grows, so do questions about what constitutes local food and what characterizes local food systems. What Is the Issue? This study provides a comprehensive literature-review-based overview of the current understanding of local food systems, including: alternative defi nitions; estimates of market size and reach; descriptions of the characteristics of local food consumers and producers; and an examination of early evidence on the economic and health impacts of such systems. What Did the Study Find? There is no generally accepted definition of “local” food. Though “local” has a geographic connotation, there is no consensus on a definition in terms of the distance between production and consumption. Definitions related to geographic distance between production and sales vary by regions, companies, consumers, and local food markets. According to the definition adopted by the U.S. Congress in the 2008 Food, Conservation, and Energy Act,the total distance that a product can be transported and still be considered a “locally or regionally produced agricultural food product” is less than 400 miles from its origin, or within the State in which it is produced. Definitions based on market arrangements, including direct-to-consumer arrangements such as regional farmers’ markets, or direct-to-retail/foodservice arrangements such as farm sales to schools, are well-recognized categories and are used in this report to provide statistics on the market development of local foods. Local food markets account for a small but growing share of total U.S. agricultural sales. • Direct-to-consumer marketing amounted to $1.2 billion in current dollar sales in 2007, according to the 2007 Census of Agriculture, compared with$551 million in 1997. • Direct-to-consumer sales accounted for 0.4 percent of total agricultural sales in 2007, up from 0.3 percent in 1997. If nonedible products are excluded from total agricultural sales, direct-to consumer sales accounted for 0.8 percent of agricultural sales in 2007. • The number of farmers’ markets rose to 5,274 in 2009, up from 2,756 in 1998 and 1,755 in 1994, according to USDA’s Agricultural Marketing Service. • In 2005, there were 1,144 community-supported agriculture organizations, up from 400 in 2001 and 2 in 1986, according to a study by the National Center for Appropriate Technology. In early 2010, estimates exceeded 1,400, but the number could be much larger. • The number of farm to school programs, which use local farms as food suppliers for school meals programs and promote relationships between schools and farms, increased to 2,095 in 2009, up from 400 in 2004 and 2 in the 1996-97 school year, according to the National Farm to School Network. Data from the 2005 School Nutrition and Dietary Assessment Survey, sponsored by USDA’s Food and Nutrition Service, showed that 14 percent of school districts participated in Farm to School programs, and 16 percent reported having guidelines for purchasing locally grown produce. Production of locally marketed food is more likely to occur on small farms located in or near metropolitan counties. Local food markets typically involve small farmers, heterogeneous products, and short supply chains in which farmers also perform marketing functions, including storage, packaging, transportation, distribution, and advertising. According to the 2007 U.S. Census of Agriculture, most farms that sell directly to consumers are small farms with less than $50,000 in total farm sales, located in urban corridors of the Northeast and the West Coast. In 2007, direct-to-consumer sales accounted for a larger share of sales for small farms, as defi ned above, than for medium-sized farms (total farm sales of$50,000 to $499,999) and large farms (total farm sales of$500,000 or more). Produce farms engaged in local marketing made 56 percent of total agricultural direct sales to consumers, while accounting for 26 percent of all farms engaged in direct-to-consumer marketing. Direct-to-consumer sales are higher for the farms engaged in other entrepreneurial activities, such as organic production, tourism, and customwork (planting, plowing, harvesting, etc. for others), than for other farms. In 2007, direct sales by all U.S. farms surpassed customwork to become the leading on-farm entrepreneurial activity in terms of farm household participation. Barriers to local food-market entry and expansion include: capacity constraints for small farms and lack of distribution systems for moving local food into mainstream markets; limited research, education, and training for marketing local food; and uncertainties related to regulations that may affect local food production, such as food safety requirements. Consumers who value high-quality foods produced with low environmental impact are willing to pay more for locally produced food. Several studies have explored consumer preferences for locally produced food. Motives for “buying local” include perceived quality and freshness of local food and support for the local economy. Consumers who are willing to pay higher prices for locally produced foods place importance on product quality, nutritional value, methods of raising a product and those methods’ effects on the environment, and support for local farmers. Federal, State, and local government programs increasingly support local food systems. Many existing government programs and policies support local food initiatives, and the number of such programs is growing. Federal policies have grown over time to include the Community Food Project Grants Program, the WIC Farmers’ Market Nutrition Program, Senior Farmers’ Market Nutrition Program, Federal State Marketing Improvement Program, National Farmers’ Market Promotion Program, Specialty Crop Block Grant Program, and the Community Facilities Program. State and local policies include those related to farm-to-institution procurement, promotion of local food markets, incentives for low-income consumers to shop at farmers’ markets, and creation of State Food Policy Councils to discuss opportunities and potential impact of government intervention. (WIC is the acronym for the Special Supplemental Nutrition Program for Women, Infants, and Children). As of early 2010, there were few studies on the impact of local food markets on economic development, health, or environmental quality. • Empirical research has found that expanding local food systems in a community can increase employment and income in that community. • Empirical evidence is insuffi cient to determine whether local food availability improves diet quality or food security. • Life-cycle assessments—analyses of energy use at all stages of the food system including consumption and disposal—suggest that localization can but does not necessarily reduce energy use or greenhouse gas emissions. How Was the Study Conducted? Existing analyses of local food markets by universities, government agencies, national nonprofit organizations, and others of local food markets were synthesized to evaluate the definition of local foods and the effects of local food systems on economic development, health and nutrition, food security, and energy use and greenhouse gas emissions. The report’s content relies on data collected through the 2007 Census of Agriculture, as well as other surveys by USDA’s Agricultural Marketing Service, the National Farm to School Network, university extension departments, and others, to provide a comprehensive picture of types of local food markets, their characteristics, and their importance over time.Local food systems; farmers’ markets; direct-to-consumer marketing; direct-to-retail/foodservice marketing; community supported agriculture; farm to school programs; Farmers’ Market Promotion Program; food miles; ERS; USDA