VOLUME 39 , ISSUE 1 (March 2019) - List of articles

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Networks of Canadian Business Elites: Historical Corporate Interlock Networks circa 1912

Jon MacKay

Abstract This paper provides details about a historical dataset of Canadian corporations and business elites who served on corporate boards circa 1912. The source of this corporate interlock data is the Directory of Directors in Canada, 1912, a public domain volume listing Canadian public companies in Canada. Because these data are thought to be of interest not only to network researchers, but also to business historians and management scholars, an attempt has been made to make the data as easy (..)

DOI: 10.21307/connections-2019-001

Signed Networks for the US Supreme Court Overturning its Prior Decisions

Patrick Doreian/ Andrej Mrvar

Abstract This paper introduces the idea of studying the decision citation network of the US Supreme Court in a new fashion by focusing on this Court’s overturning of some of its prior decisions. Two departures from current practices were developed. One was to consider the phenomenon of overturning in a broader network context. The second was to treat the citations between overturning decisions and the overturned decisions as negative ties. This led to the creation of multiple signed citation net(..)

DOI: 10.21307/connections-2019-002

What the eye does not see: visualizations strategies for the data collection of personal networks

Isidro Maya-Jariego/ Romina Cachia

Abstract The graphic representation of relational data is one of the central elements of social network analysis. In this paper, the author describe the use of visualization in interview-based data collection procedures designed to obtain personal networks information, exploring four main contributions. First, the author shows a procedure by which the visualization is integrated with traditional name generators to facilitate obtaining information and reducing the burden of the interview process.(..)

DOI: 10.21307/connections-2019-003

Who Dunnit: The Party Mystery Game for Analyzing Network Structure and Information Flow

Seungyoon Lee/ Zachary Wittrock/ Bailey C. Benedict

Abstract The activity facilitates students’ understanding of network measures, including different types of node centrality, shortest paths, cliques, and communities, and their implications for information flow in groups or organizations. The goal of the game is for students (a minimum of 10 and maximum of 28 participants in a network; a larger class can be divided into two or more networks) to solve a company mystery by exchanging information clues with other students based on an imposed commun(..)

DOI: 10.21307/connections-2019-005

Mapping Gray Maritime Networks

Wayne Porter/ Rob Schroeder/ Chris Callaghan/ Albert Barreto/ Sam Bussell/ Brian Young/ Manuel Loewer/ Daniel Funk/ Janet von Eiff

Abstract This research focused on the identification and tracking of subgroups of vessels of interest, owners, operators, ports, cargoes, and specific activities associated with artificial reef enhancement and construction in the South China Sea. Historical automated information system (AIS) tracks and current maritime databases were used to develop sociogram depictions of the gray (licit but only partially transparent) maritime network that connects these nodes (ships, events, organizations, po(..)

DOI: 10.21307/connections-2019-006

Linton C. Freeman Interview by Katherine Faust, July 27, 2018

Katherine Faust

Abstract At the business meeting of the International Network for Social Network Analysis (INSNA) in June 2018, there was great enthusiasm for conducting and archiving interviews with luminaries in the field. Lin Freeman’s name was mentioned, and I was drafted to conduct the interview. This is an edited transcript of the interview that I conducted with Lin on July 27, 2018. Lin passed away three weeks later, on August 17, 2018. He was 91 years old.

DOI: 10.21307/connections-2019-004

Mapping the Distribution and Spread of Social Ties Over Time: A Case Study Using Facebook Friends

Clio Andris/ Sara E. Cavallo/ Elizabeth A. Dzwonczyk/ Laura Clemente-Harding/ Carolynne Hultquist/ Marie Ozanne

Abstract Relational geography asserts that social networks provide geographic benefits, and geographies are transmitted through the sharing of local knowledge and experience. To articulate the spatial expanse and geographic benefits of an individual’s social network, researchers require better social-spatial geographic information system models illustrating how contacts are dispersed, and how many distinct places they inhabit. In this work, the authors conduct a case study to map social network (..)

DOI: 10.21307/connections-2019-007

Ukrainian and Russian organizations in Sweden and the conflict “back home”

Sofiya Voytiv

Abstract This paper investigates whether the Maidan Revolution in Kyiv (late 2013–early 2014) and the ongoing armed conflict in Eastern Ukraine (early 2014) have been reflected in the collaboration networks of Ukrainian and Russian organizations in Sweden between 2013 and 2016. I use ERG models to account for the probabilities of ties between the organizations, depending on the network structure and individual attributes such as ethnic identification and the choice of a side to support in the co(..)

DOI: 10.21307/connections-2019-008

Hairball Buster: A Graph Triage Method for Viewing and Comparing Graphs

Patrick Allen/ Mark Matties/ Elisha Peterson

Abstract Hairball buster (HB) (also called node-neighbor centrality or NNC) is an approach to graph analytic triage that uses simple calculations and visualization to quickly understand and compare graphs. Rather than displaying highly interconnected graphs as ‘hairballs’ that are difficult to understand, HB provides a simple standard visual representation of a graph and its metrics, combining a monotonically decreasing curve of node metrics with indicators of each node’s neighbors’ metrics. The(..)

DOI: 10.21307/connections-2019-009

Academic Collaboration via Resource Contributions: An Egocentric Dataset

Michał Bojanowski,/ Dominika Czerniawska/ Wojciech Fenrich

Abstract In order to understand scientists’ incentives to form collaborative relations, we have conducted a study looking into academically relevant resources, which scientists contribute into collaborations with others. The data we describe in this paper are an egocentric dataset assembled by coding originally qualitative material. It is 40 multiplex ego networks containing data on individual attributes (such as gender, scientific degree), collaboration ties (including alter–alter ties), and re(..)

DOI: 10.21307/connections-2019-010

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