Iberian neolithic networks: The rise and Fall of the Cardial World

Recent approaches have described the evolutionary dynamics of the rst Neolithic soci- eties as a cycle of rise and fall. Several authors, using mainly c14 dates as a demographic proxy, identi ed a general pattern of a boom in population coincident with the arrival of food production economies followed by a rapid decline some centuries afterward in multiple European regions. Concerning Iberia, we also noted that this phenomenon correlates with an initial development of archeological entities (i.e., 'cultures') over large areas (e.g., the Impresso-Cardial in West Mediterranean), followed by a phase of 'cultural fragmentation' by the end of Early Neolithic. This results in a picture of higher cultural diversity as an effect of more limited spread of cultural artifacts. In this work, we propose to apply a network approach to the analysis of material culture. In particular, we consider the spatiotemporal patterns of material culture as an emergent effect of local interaction processes. As recent research has pointed out, the spatiotemporal variability of material culture is an emergent phenomenon resulting from individual and group interactions whose structure resembles those of spatially structured complex networks. Our results suggest that the observed global patterns could be explained by the network dynamics, especially by structural (measured as the betweenness centrality) and geographical position of some nodes. The appearance and disappearance of nodes in speci c posi- tions correlate with the observed changes in the pattern of material culture distribution throughout the Early Neolithic (c. 7700-6700 cal BP) in East Iberia. In our view, this could be explained by the special role played by those nodes facilitating or limiting the information ow over the entire network. Network growth and posterior fragmentation seem to be the key drivers behind these dynamics

Foundations and modelling of dynamic networks using Dynamic Graph Neural Networks: A survey

Dynamic networks are used in a wide range of fields, including social network analysis, recommender systems, and epidemiology. Representing complex networks as structures changing over time allow network models to leverage not only structural but also temporal patterns. However, as dynamic network literature stems from diverse fields and makes use of inconsistent terminology, it is challenging to navigate. Meanwhile, graph neural networks (GNNs) have gained a lot of attention in recent years for their ability to perform well on a range of network science tasks, such as link prediction and node classification. Despite the popularity of graph neural networks and the proven benefits of dynamic network models, there has been little focus on graph neural networks for dynamic networks. To address the challenges resulting from the fact that this research crosses diverse fields as well as to survey dynamic graph neural networks, this work is split into two main parts. First, to address the ambiguity of the dynamic network terminology we establish a foundation of dynamic networks with consistent, detailed terminology and notation. Second, we present a comprehensive survey of dynamic graph neural network models using the proposed terminologyComment: 28 pages, 9 figures, 8 table

Molecular Model of Dynamic Social Network Based on E-mail communication

In this work we consider an application of physically inspired sociodynamical model to the modelling of the evolution of email-based social network. Contrary to the standard approach of sociodynamics, which assumes expressing of system dynamics with heuristically defined simple rules, we postulate the inference of these rules from the real data and their application within a dynamic molecular model. We present how to embed the n-dimensional social space in Euclidean one. Then, inspired by the Lennard-Jones potential, we define a data-driven social potential function and apply the resultant force to a real e-mail communication network in a course of a molecular simulation, with network nodes taking on the role of interacting particles. We discuss all steps of the modelling process, from data preparation, through embedding and the molecular simulation itself, to transformation from the embedding space back to a graph structure. The conclusions, drawn from examining the resultant networks in stable, minimum-energy states, emphasize the role of the embedding process projecting the non–metric social graph into the Euclidean space, the significance of the unavoidable loss of information connected with this procedure and the resultant preservation of global rather than local properties of the initial network. We also argue applicability of our method to some classes of problems, while also signalling the areas which require further research in order to expand this applicability domain

Topological robustness of the global automotive industry

The manufacturing industry is characterized by large-scale interdependent networks as companies buy goods from one another, but do not control or design the overall flow of materials. The result is a complex emergent structure with which companies connect to each other. The topology of this structure impacts the industry’s robustness to disruptions in companies, countries, and regions. In this work, we propose an analysis framework for examining robustness in the manufacturing industry and validate it using an empirical dataset. Focusing on two key angles, suppliers and products, we highlight macroscopic and microscopic characteristics of the network and shed light on vulnerabilities of the system. It is shown that large-scale data on structural interdependencies can be examined with measures based on network science

Towards A Scale Free Network Approach to Study Organizational Communication Network

In this experiment, we study the scale free network property of an organizational communication network. We used social network analysis methods during organizational crisis period that captures the dynamics of communication networks. We did not find any significant fluctuation between the actor prominence in daily and aggregated networks. We found that email communication network displays a high degree of scale free behavior described by power law

Ambiguity of Social Networks in Post-Communist Contexts

The paper discusses three hypotheses. First, it introduces four ideal types of networks which are combined in the category of networks as used by social scientists. Four types result from the intersection of two implicit choices made about networks – networks are assumed to be either personal or impersonal, and are viewed either internally or externally. Thus, networks are understood in terms of sociability, access to resources, enabling structure, or social capital. Second, I argue that networks function in a fundamentally ambiguous way. They operate in their capacity of a safety net or survival kit, provide a ‘beating the system’ capacity or compensate for the system’s defects. At the same time networks provide constraints such as high costs of informal contract, limits on individual action, lock-in effects and the handicaps of social capital. Third, I illustrate differences between networks serving the economy of favors in Russia and networks serving the purposes of ‘network society.

Firm's Network versus Board Members' Network: Who to Appoint?

A crucial question at the center of corporate governance theories and of the literature on social networks alike is the sense of empower of prestige, or influence on the actors of a social network. This paper approaches the possibility of measuring this influence by detecting key individuals who support network dynamics. By means of a study conducted on a sample of CAC 40 directors, it will be shown that the most influential elements are not necessarily the best placed at the beginning. Contrary to all expectations, a dynamics of influence is based on criteria of indispensability to the network that will be presented as an example

Data governance through a multi-DLT architecture in view of the GDPR

The centralization of control over the processing of personal data threatens the privacy of individuals due to the lack of transparency and the obstruction of easy access to their data. Individuals need the tools to effectively exercise their rights, enshrined in regulations such as the European Union General Data Protection Regulation (GDPR). Having direct control over the flow of their personal data would not only favor their privacy but also a “data altruism”, as supported by the new European proposal for a Data Governance Act. In this work, we propose a multi-layered architecture for the management of personal information based on the use of distributed ledger technologies (DLTs). After an in-depth analysis of the tensions between the GDPR and DLTs, we propose the following components: (1) a personal data storage based on a (possibly decentralized) file storage (DFS) to guarantee data sovereignty to individuals, confidentiality and data portability; (2) a DLT-based authorization system to control access to data through two distributed mechanisms, i.e. secret sharing (SS) and threshold proxy re-encryption (TPRE); (3) an audit system based on a second DLT. Furthermore, we provide a prototype implementation built upon an Ethereum private blockchain, InterPlanetary File System (IPFS) and Sia and we evaluate its performance in terms of response time

Ubiquitous Computing

The aim of this book is to give a treatment of the actively developed domain of Ubiquitous computing. Originally proposed by Mark D. Weiser, the concept of Ubiquitous computing enables a real-time global sensing, context-aware informational retrieval, multi-modal interaction with the user and enhanced visualization capabilities. In effect, Ubiquitous computing environments give extremely new and futuristic abilities to look at and interact with our habitat at any time and from anywhere. In that domain, researchers are confronted with many foundational, technological and engineering issues which were not known before. Detailed cross-disciplinary coverage of these issues is really needed today for further progress and widening of application range. This book collects twelve original works of researchers from eleven countries, which are clustered into four sections: Foundations, Security and Privacy, Integration and Middleware, Practical Applications