Suchergebnisse

The article examines all the different judicial aspects of the response which was given by the Republic of Venice to the serious revolution exploded in Crete in 1363. From the legal point of view, this response was structured on the procedures of exception (inquisitio ex officio, arbitrium, privilege and grace) normally applied in late Middle Ages as effective means to preserve political authority. These procedures were used by Venice as flexible elements to create consent and to legitimate its power. ; Il contributo esamina gli aspetti giudiziari della risposta che la Repubblica di Venezia pianificò per fronteggiare e reprimere la gravissima insurrezione esplosa a Creta nel 1363. Tale risposta si articolò principalmente su procedure giudiziarie extra-ordinarie (inquisitio ex officio, dilatazione dell'arbitrium iudicis, grazia e privilegio), commisurate alla natura degli avvenimenti e dispiegate al fine di legittimare la sovranità veneziana a Creta in seguito alla sua messa in discussione surrettizia da parte dei ribelli.

Traditional methods to study visual politics have been limited in geographical, media and temporal coverage. Recent advances in deep learning have the potential to dramatically extend the scope of the field especially with respect to making sense of the contemporary social and political developments in digital media. While some early adopters may be tempted to take the new computational tools at face value, others see their black-box character as cause for concern. This paper argues that the integration of deep learning into the study of visual politics must be approached still more critically and boldly. On the one hand, the complexity of visual political themes requires a more substantial human involvement if compared with other applications of deep neural networks. Therefore, a question is how the scientist and the network should best interact. On the other hand, it is important to acknowledge that a deep learning tool will never simply replace specific tasks inside a research pro- cess: its adoption has implications for the broader process from the delineation of the object of analysis, to data collection, to the interpretation and communication of results. We examine the conditions of integrating a deep learning tool for image classification into the large-scale study of visual politics in digital and social media along these two dimensions.

During the last century, networks of several types have been used to model a wide range of physical, biological and social systems. For example, Moreno (1934) studied social networks with multiple types of ties, later called multiplex networks (Verbrugge, 1979; Minor, 1983; Lazega & Pattison, 1999) as well as networks with multiple types of actors. Networks with multiple types of actors and relational ties have often been used together: relevant examples are the extensions of two-mode networks studied by Wasserman & Iacobucci (1991), multi-level networks (Lazega & Snijders, 2016), and heterogeneous information networks (Sun et al., 2012). More recently, researchers in physics and computer science have developed models for different types of interconnected networks known as networks of networks (Buldyrev et al., 2010; D'Agostino & Scala, 2014), multilayer social networks (Magnani & Rossi, 2011), and interconnected networks (Dickison et al., 2012).

"This book covers the modeling, analysis and mining of systems made of multilayer social networks, from groups of individuals connected through different types of relationships to large systems of multiple online social network sites. A range of practical and theoretical topics are covered, from data collection, pre-processing, measuring and mining to theoretical models behind the evolution of interconnected social networks and dynamical processes like information spreading"--

Multilayer networks, in particular multilayer social networks, where users belong to and interact on different networks at the same time, are an active research area in social network analysis, computer science, and physics. These networks have traditionally been studied within these separate research communities, leading to the development of several independent models and methods to deal with the same set of problems. This book unifies and consolidates existing practical and theoretical knowledge on multilayer networks including data collection and analysis, modeling, and mining of multilayer social network systems, the evolution of interconnected social networks, and dynamic processes such as information spreading. A single real dataset is used to illustrate the concepts presented throughout the book, demonstrating both the practical utility and the potential shortcomings of the various methods. Researchers from all areas of network analysis will learn new aspects and future directions of this emerging field

AbstractClustering a graph, i.e., assigning its nodes to groups, is an important operation whose best known application is the discovery of communities in social networks. Graph clustering and community detection have traditionally focused on graphs without attributes, with the notable exception of edge weights. However, these models only provide a partial representation of real social systems, that are thus often described using node attributes, representing features of the actors, and edge attributes, representing different kinds of relationships among them. We refer to these models asattributed graphs. Consequently, existing graph clustering methods have been recently extended to deal with node and edge attributes. This article is a literature survey on this topic, organizing, and presenting recent research results in a uniform way, characterizing the main existing clustering methods and highlighting their conceptual differences. We also cover the important topic of clustering evaluation and identify current open problems.

This article examines the principles outlined in the General Data Protection Regulation in the context of social network data. We provide both a practical guide to General Data Protection Regulation--compliant social network data processing, covering aspects such as data collection, consent, anonymization, and data analysis, and a broader discussion of the problems emerging when the general principles on which the regulation is based are instantiated for this research area.