“What do interlocks do” revisited – a bibliometric analysis

PurposeIt has been over 20 years since the landmark publication of Mizruchi (1996) and his examination of “what do interlocks do?”. Since then, the nature of interlocks and subsequent research on the subject has evolved. This paper aims to revisit the literature on interlocking directorates through a quantitative bibliometric analysis.Design/methodology/approachThis study undertakes a bibliometric analysis of literature citing the Mizruchi (1996) to examine the state of research following up on “what do interlocks do”. This study examines 718 publications using keyword and co-word analysis, along with a thematic analysis to revisit the research that has followed Mizruchi’s topic of what do interlocks do.FindingsThis study finds that the topics of the corporate elite, capitalist economy and corporate governance have remained prominent themes in the field. Research areas that are emerging in the field of interlocking directorates include gender diversity, globalisation and advancing theoretical frameworks.Originality/valueThis paper provides a quantitative bibliometric analysis to revisit the extant literature on “what do interlocks do”, examining a high number of articles to identify areas which could be developed to advance research in the field

Efficiently Counting Complex Multilayer Temporal Motifs in Large-Scale Networks

This paper proposes novel algorithms for efficiently counting complex network motifs in dynamic networks that are changing over time. Network motifs are small characteristic configurations of a few nodes and edges, and have repeatedly been shown to provide insightful information for understanding the meso-level structure of a network. Here, we deal with counting more complex temporal motifs in large-scale networks that may consist of millions of nodes and edges. The first contribution is an efficient approach to count temporal motifs in multilayer networks and networks with partial timing, two prevalent aspects of many real-world complex networks. We analyze the complexity of these algorithms and empirically validate their performance on a number of real-world user communication networks extracted from online knowledge exchange platforms. Among other things, we find that the multilayer aspects provide significant insights in how complex user interaction patterns differ substantially between online platforms. The second contribution is an analysis of the viability of motif counting algorithms for motifs that are larger than the triad motifs studied in previous work. We provide a novel categorization of motifs of size four, and determine how and at what computational cost these motifs can still be counted efficiently. In doing so, we delineate the “computational frontier” of temporal motif counting algorithms.Algorithms and the Foundations of Software technolog

Multiplex network motifs as building blocks of corporate networks

Abstract In corporate networks, firms are connected through links of corporate ownership and shared directors, connecting the control over major economic actors in our economies in meaningful and consequential ways. Most research thus far focused on the connectedness of firms as a result of one particular link type, analyzing node-specific metrics or global network-based methods to gain insights in the modelled corporate system. In this paper, we aim to understand multiplex corporate networks with multiple types of connections, specifically investigating the network’s essential building blocks: multiplex network motifs. Motifs, which are small subgraph patterns occurring at significantly higher frequencies than in similar random networks, have demonstrated their usefulness in understanding the structure of many types of real-world networks. However, detecting motifs in multiplex networks is nontrivial for two reasons. First of all, there are no out-of-the-box subgraph enumeration algorithms for multiplex networks. Second, existing null models to test network motif significance, are unable to incorporate the interlayer dependencies in the multiplex network. We solve these two issues by introducing a layer encoding algorithm that incorporates the multiplex aspect in the subgraph enumeration phase. In addition, we propose a null model that is able to preserve the interlayer connectedness, while taking into account that one of the link types is actually the result of a projection of an underlying bipartite network. The experimental section considers the corporate network of Germany, in which tens of thousands of firms are connected through several hundred thousand links. We demonstrate how incorporating the multiplex aspect in motif detection is able to reveal new insights that could not be obtained by studying only one type of relationship. In a general sense, the motifs reflect known corporate governance practices related to the monitoring of investments and the concentration of ownership. A substantial fraction of the discovered motifs is typical for an industrialized country such as Germany, whereas others seem specific for certain economic sectors. Interestingly, we find that motifs involving financial firms are over-represented amongst the larger and more complex motifs. This demonstrates the prominent role of the financial sector in Germany’s largely industry-oriented corporate network