Network theory

About: Network theory is a research topic. Over the lifetime, 2257 publications have been published within this topic receiving 109864 citations.

The Impacts of Social Networking and Its Analysis

Abstract: Social networking sites are playing very significant role in today time; it has a direct impact on all age group people. Though it has many cons but still these are like an effective tool in communicating millions of people and spreading our expressions and view worldwide. We all need a change in the pattern of use, in order to prevent miss- happenings on these sites. If we will be active and aware these sites will serve us their batter and will bring some more revolution in the world of cyber technology. Social network analysis (SNA) is the methodical analysis of social networks. Social network analysis views social relationships in terms of network theory, consisting of nodes (representing individual actors within the network) and ties (which represent relationships between the individuals, such as friendship, kinship, organizational position etc.). These networks are often depicted in a social network diagram, where nodes are represented as points and ties are represented as lines.

A method to characterize the social cascading damage processes of disasters using media information

Abstract: Constantly advancing media information is a key data source to characterize the social cascading damage processes following natural hazards. However, media information tends to include a large sample size but low information density. In consideration of these properties, the aim of this study is to develop a new method for media-based information characterizing social cascading damage processes. In developing the method, a network theory framework was constructed to systematically integrate media information and its characterization. The method has two analytical components: a disaster damage network systematically inputting media information and network analysis using the concept of degree centrality. The developed method was applied to the record-breaking 2018 heavy rain disaster in western Japan, employing newspaper articles as media information sources. The study identified the critical disaster events and their relationships. This case study demonstrates that our method will benefit policymakers by providing them with potential fundamental information to support disaster management.

Centrality measures in interval-weighted networks

Abstract: Abstract Centrality measures are used in network science to assess the centrality of vertices or the position they occupy in a network. There are a large number of centrality measures according to some criterion. However, the generalizations of the most well-known centrality measures for weighted networks, degree centrality, closeness centrality and betweenness centrality have solely assumed the edge weights to be constants. This article proposes a methodology to generalize degree, closeness and betweenness centralities taking into account the variability of edge weights in the form of closed intervals (interval-weighted networks, IWN). We apply our centrality measures approach to two real-world IWN. The first is a commuter network in mainland Portugal, between the 23 NUTS 3 Regions. The second focuses on annual merchandise trade between 28 European countries, from 2003 to 2015.

Food Supply Chains and Eva.CAN Model: a Network Analytic Approach

Abstract: The research work leading to the drafting of this PhD thesis approaches the analysis of supply chains of products of animal origin from various productive species by using network analytic methods. In the studied analysis six supply chains are embedded in a single model which highlights all the interconnections that have little evidence in traditional models. This new model that we called Eva.CAN (Evaluation of Complex Agri-food Network Model) is a new concept model, the first complex network model for the agri-food production, the first to allow the application of Network Theory analysis methods. The initial hypothesis is that the various supply chains of products of animal origin have to be interpreted and analyzed as a whole, as a single complex system. The complex network is studied analyzing the adjacency matrix that constitutes the network with algorithms and methods extensively tested and validated. This analytical approach has already been applied with positive results in many research areas such as social networks, transport networks, the stylistic of writers and musicians, proteomics, pharmacology, medicine, biology, and many others. We apply this methodology to supply chains of products of animal origin and show a series of preliminary results. This method of study of food supply chains could be useful for an observatory, bringing to light slightly evident relations and becoming a strong support for policy-makers. It can also provide useful advices to individual actors on how to optimize their own supply chains. Finally, through an effective enumeration and evaluation of the relationships, a network model could be helpful in design of tracking and traceability systems.

'M-C-K' Group Actor Network Model and Knowledge Production Mechanism of Interdisciplinary Innovation Team

Abstract: Interdisciplinary innovation team is an important organization for contemporary knowledge productionBased on Actor-Network Theory and Knowledge Network Theory,the paper builds a 'material network-knowledge network-cultural network(M-C-K)' coupling actor network model and group actor network model of interdisciplinary innovation team,analyzes 'M-C-K' network co-evolutionary mechanism of interdisciplinary innovation team's knowledge production,points out the process,forms and powers of interdisciplinary innovation team's knowledge production