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The authors study the interdisciplinary relation between graph and algebraic structure ring defining a new graph, namely “non-essential sum graph”. The nonessential sum graph, denoted by NES(R), of a commutative ring R with unity is an undirected graph whose vertex set is the collection of all nonessential ideals of R and any two vertices are adjacent if and only if their sum is also a nonessential ideal of R.

The method is theoretical.

The authors obtain some properties of NES(R) related with connectedness, diameter, girth, completeness, cut vertex, r-partition and regular character. The clique number, independence number and domination number of NES(R) are also found.

The paper is original.

The purpose of this study is twofold; first, it aims to understand the underlying dynamics of the organizations behind the terrorist attacks, and second, to investigate the dynamics of terrorist organizations in relation to one another to detect whether there exist shared patterns of terror between different organizations.

To achieve this purpose, the researcher proposes a computational algorithm that extracts data from global terrorism database (GTD); calculates similarity indices between different terrorist groups; generates a network data file from the calculated indices; and apply network analysis techniques to the extracted data. The proposed algorithm includes applying SQL database codes for data extraction, building a tailored C# computer software to calculate similarity indices and generate similarity networks and using GEPHI software to visualize the generated network and calculate network metrics and measures.

Applying the proposed algorithm to Egypt, the results reveal different shared patterns of terror among different terrorist groups. This helps us in creating a terror landscape for terrorist groups playing in Egypt.

The importance of the study lies in that it proposes a new algorithm that combines network analysis with other data-manipulation techniques to generate a network of similar terror groups.

This paper presents a critical review of the economic network analysis methods and their applications to maritime transport. A network can be presented in terms of its structure, topology, characteristics as well as the connectivity with different measures such as density, degree distribution, centrality (degree, betweenness, closeness, eigenvector and strength), clustering coefficient, average shortest path length and assortative. Various models such as the random graph model, block model, and ERGM can be used to analyse and explore the formation of a network and interaction between nodes. The review of the existing theories and models has found that, while these models are rather computationally intensive, they are based on some rather restrictive assumption on network formation and relationship between ports in the network at the local and global levels that require further investigation. Based on the review, a conceptual framework for maritime transport network research is developed, and the applications for future research are also discussed.

This paper presents a critical review of the economic network analysis methods and their applications to maritime transport. A network can be presented in terms of its structure, topology, characteristics as well as the connectivity with different measures such as density, degree distribution, centrality (degree, betweenness, closeness, eigenvector and strength), clustering coefficient, average shortest path length and assortative. Various models such as the random graph model, block model, and ERGM can be used to analyse and explore the formation of a network and interaction between nodes. The review of the existing theories and models has found that, while these models are rather computationally intensive, they are based on some rather restrictive assumption on network formation and relationship between ports in the network at the local and global levels that require further investigation. Based on the review, a conceptual framework for maritime transport network research is developed, and the applications for future research are also discussed.

The purpose of this paper is to review the recent studies on opinion polarization and disagreement.

In this work, recent advances in opinion polarization and disagreement and pay attention to how they are evaluated and controlled are reviewed.

In literature, three metrics: polarization, disagreement and polarization-disagreement index are usually adopted and there is a tradeoff between polarization and disagreement. Different strategies have been proposed in literature which can significantly control opinion polarization and disagreement based on these metrics.

This review is of crucial importance to summarize works on opinion polarization and disagreement and to the better understanding and control of them.

This paper aims to provide information about the structure of collaborative work among Argentinian economics. The study provides specific applied research of social network analysis focus on this profession in this specific country.

The contribution opted for applying social network analysis tools to papers presented in a congress and published in its proceedings. The authors focus in detecting main actors, groups of co-authorship, professionals acting as bridges between groups and differences between genders.

The paper provides empirical insights about how co-authorship has evolved between Argentine economists. The authors find that structural properties of the network, main actors, both male and female, main universities or center that affiliates them, a gender gap that might be closing out.

The paper focuses on the network for the period 1964-2014 without a more detailed dynamic. It also does not explain main topics worked by the authors.

The work provides knowledge about how groups are created in Economics in Argentina, how cooperation has evolved and what has been the role of women in this development. It also shows how different departments and entities collaborate with diverse success in the creation of new knowledge in Economics in Argentina.

The paper works with data from a source of information non-previously studied and contributes in explaining a particular type of collaborative work in a profession in Argentina.

To help ensure that children with social and behavioral health problems get the support services they need, organizations collaborate in cross-sectoral networks. In this article, the authors explore and compare the structure of these complex child service delivery networks in terms of differentiation (composition) and integration (interconnection). In particular, the authors investigate the structure of client referral and identify which organizations are most prominent within that network structure and could therefore fulfill a coordinating role.

The authors used a comparative case study approach and social network analysis on three interorganizational networks consisting of 65 to 135 organizations within the Dutch child service delivery system. Semi-structured interviews with the network managers were conducted, and an online questionnaire was sent out to the representatives of all network members.

The networks are similarly differentiated into 11 sectors with various tasks. Remarkably, network members have contact with an average of 20–26 organizations, which is a fairly high number to be handled successfully. In terms of integration, the authors found a striking diversity in the structures of client referral and not all organizations with a gatekeeper task hold central positions.

Due to the scarcity of comparative whole network research in the field, the strength of this study is a deeper understanding of the differentiation and integration of complex child service delivery systems. These insights are crucial in order to deliver needed services and to minimize service silos and fragmentation.