Use Of Network Analysis Techniques Research Articles

Network analysis of international export pattern.

There is a relationship between the trade flows of the countries and their economic growth potential and development. One way to analyze the trade flows of countries with each other is the use of network analysis techniques. Network analysis uses a visual, mathematical and statistical approach to identify and quantify the structural properties of networks. In this study, the relationship of the first 50 countries in the world in terms of export volume was evaluated with Gephi 0.9.2, one of the social network analysis programs. The effect of the COVID-19 epidemic disease on the commercial flows of the countries is the main purpose of the study. The existence of the effective role of geographic proximity in commercial flows, the commercial partners of the countries, the centrality criteria and the existence of countries that have an active role in the world are clarified with this study.

Extracting multilayer networks from Sentinel-2 satellite image time series

AbstractNowadays, modern Earth Observation systems continuously generate huge amounts of data. A notable example is the Sentinel-2 Earth Observation mission, developed by the European Space Agency as part of the Copernicus Programme, which supplies images from the whole planet at high spatial resolution (up to 10 m) with unprecedented revisit time (every 5 days at the equator). In this data-rich scenario, the remote sensing community is showing a growing interest toward modern supervised machine learning techniques (e.g., deep learning) to perform information extraction, often underestimating the need for reference data that this framework implies. Conversely, few attention is being devoted to the use of network analysis techniques, which can provide a set of powerful tools for unsupervised information discovery, subject to the definition of a suitable strategy to build a network-like representation of image data. The aim of this work is to provide clues on how Satellite Image Time Series can be profitably represented using complex network models, by proposing a methodology to build a multilayer network from such data. This is the first work to explore the possibility to exploit this model in the remote sensing domain. An example of community detection over the provided network in a real-case scenario for the mapping of complex land use systems is also presented, to assess the potential of this approach.

Graph theory reveals amygdala modules consistent with its anatomical subdivisions

Similarities on the cellular and neurochemical composition of the amygdaloid subnuclei suggests their clustering into subunits that exhibit unique functional organization. The topological principle of community structure has been used to identify functional subnetworks in neuroimaging data that reflect the brain effective organization. Here we used modularity to investigate the organization of the amygdala using resting state functional magnetic resonance imaging (rsfMRI) data. Our goal was to determine whether such topological organization would reliably reflect the known neurobiology of individual amygdaloid nuclei, allowing for human imaging studies to accurately reflect the underlying neurobiology. Modularity analysis identified amygdaloid elements consistent with the main anatomical subdivisions of the amygdala that embody distinct functional and structural properties. Additionally, functional connectivity pathways of these subunits and their correlation with task-induced amygdala activation revealed distinct functional profiles consistent with the neurobiology of the amygdala nuclei. These modularity findings corroborate the structure–function relationship between amygdala anatomical substructures, supporting the use of network analysis techniques to generate biologically meaningful partitions of brain structures.

Exploring behavioral information security networks in an organizational context: An empirical case study

The purpose of this research is to propose network research as an alternative approach in the behavioral security field. A case study was conducted in a large interior contractor to explore eight organizational networks, four of which focus on security behaviors. The researchers employed social network analysis methods, including quantitative and qualitative ones, to analyze the case study's data and demonstrate the analytical capability of the network analysis approach in the behavioral security field. Key features of the security networks' structures include high transitivity, hierarchy, and centralization, whereas reciprocity and density are lower than other organizational networks. Moreover, work-related interactions were found to impact security influence, among which giving IT advice increases significantly one's influential status in security matters. Practical implications include suggestions about the use of network analysis methods as a tool for security managers to monitor their behavioral security networks and devise appropriate strategies. Potential research directions are also elaborated, which future research can employ and promote the novel and practical use of network analysis techniques.

Network analysis of wildlife translocations in New Zealand

AIMS: To identify network measures with relevance to disease spread in a network of movements derived from the Department of Conservation (DOC) translocation records from 1970 to mid-2014, and to identify conservation sites that should be prioritised for surveillance activities and improvements to data collection to make the best use of network analysis techniques in the future.METHODS: Data included the source and destination of translocated specimens, the species and the dates the translocations were expected to occur. The data were used to construct a directed, non-weighted network in which a translocation event represented a tie in the network. Network density, in-degree (movements entering a node of interest) and out-degree (movements leaving a node of interest) and reciprocity were calculated.RESULTS: The data analysed consisted of 692 unique translocations between 307 sites, with the majority (518; 73%) being for birds. The constructed network for bird, reptile and frog translocations comprised 260 nodes, with 34/260 (13%) having two-way movements and 47/260 (18%) non-reciprocal movements. The median degree score (sum of in- and out-degree) was two (min 0, max 36) with a mean of 3.5 in a right skewed distribution. Most sites acted as receivers or senders of consignments with only a few having both high in- and high out-degree, and thus had characteristics that made them sites of interest for surveillance activities. These included the National Wildlife Centre at Mount Bruce, Tiritiri Matangi Island and Te Kakahu (Chalky Island).CONCLUSIONS: The presence of linking sites that join larger clusters within the network creates the potential for rapid disease spread if a pathogen were to be introduced. The important sites that supply or receive specimens for translocations are already well recognised by those performing translocations in New Zealand, and this paper provides further information by quantifying their role within the network.

Comments on the use of network structures to analyse commercial companies’ evolution and their impact on economic behaviour

Network analysis studies the development of the social structure of relationships around a group or an institutional body, and how it affects beliefs and behaviours. Causal constraints require a special and deeper attention to the social structure. The purpose of this paper is to give a new approach to the idea that this reality should be primarily conceived and investigated from the perspective of the properties of relations between and within units, instead of the properties of these units themselves. The relationship may refer to the exchange of products, labour, information and money. By mapping these relationships, network analysis can help to uncover the emergent and informal communication patterns of commercial companies that may be compared to the formal communication structures. These emergent patterns can be used to explain institutional and individuals’ behaviours. Network analysis techniques focus on the communication structure of an organization that can be subdivided and handled with different approaches. Structural features that can be analysed through the use of network analysis techniques are, for example, the (formal and informal) communication patterns in an organization or the identification of specific groups within an organization. Special attention may be given to specific aspects of communication patterns.

Current and future use of systems analysis in water distribution network design

Abstract Computer use in the design of water distribution networks was inititated through the use of network analysis techniques to determine system performance in terms of heads and flows. The last fifteen years, however, have seen the introduction of systems analysis optimization techniques to the range of computer models available for network design purposes. These optimization models differ markedly from the ‘traditional’ network analysis models in that they ‘design’ systems for specified loading conditions rather than just analysing the performance of predetermined systems under given loading conditions. Cost was the primary or only objective in almost all these early optimization models. Water distribution network design has, however, a number of other important objectives, such as maximizing reliability. Issues related to reliability concern include probability of component failure, probability of actual demands being greater than design values, and the system redundancy inherent within the layout ...

Health‐Seeking Behavior and Social Networks of the Aged Living in Single‐Room Occupancy Hotels

The elderly who reside in single-room occupancy (SRO) hotels often have been depicted as "isolates," lacking the interest or ability to engage primary or secondary support systems. This characterization has not enhanced understanding of how the SRO aged are able to survive in the community. With the use of network analysis techniques, this study demonstrates the inaccuracy of the assertion that these old persons lack significant social support. The data pointed to differences in network size, complexity, intensity, connectedness, and directionality in relation to varying degrees of physical and psychiatric health.