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Vol. 2 - Graphs and social systems
1. Introduction to the special issue on Graphs & Social Systems
The principle of the Journal of Interdisciplinary Methodologies and Issues in Science (JIMIS) is that each issue is a special one, dedicated to a specific topic and handled by guest editors. This issue (the second of the journal) focuses on the use of graphs (and associated analysis tools) to model and study social systems. The guest editors for this issue are Rosa Figueiredo and Vincent Labatut.
Section:
Subject Area 3: Graphs and Networks
2. Reflections on Studying Signed Networks
Despite considerable success, the balance theoretic approach to studying signed relations has encountered some serious problems, both substantive and methodological. The more consequential of them are outlined along with reasons for why solving them is critical. In essence, an agenda of research problems is laid out with many juicy problems to solve. These reflections, while setting a context in prior work, are far more concerned about looking to the future and identifying problems whose solutions hold the potential for transforming the field.
Section:
Subject Area 3: Graphs and Networks
3. Analyse des Préférences et Tournois Pondérés
Dans de nombreuses etudes expérimentales , on dispose de n ´ eléments ordonnés suivant plusieurs classements (votes, notes ou crit eres). Nous traitons et comparons deuxprobì emes : (i) Etablir un classement unique (ordre total) des n items et (ii) sélectionner les k meilleurs eléments parmi n. Il s'agit, dans les deux cas, de minimiser le nombre de préférences qui vont a l'encontre de ces 5 choix.
Section:
Subject Area 3: Graphs and Networks
4. Brazilian Congress structural balance analysis
In this work, we study the behavior of Brazilian politicians and political parties with the help of clustering algorithms for signed social networks. For this purpose, we extract and analyze a collection of signed networks representing voting sessions of the lower house of Brazilian National Congress. We process all available voting data for the period between 2011 and 2016, by considering voting similarities between members of the Congress to define weighted signed links. The solutions obtained by solving Correlation Clustering (CC) problems are the basis for investigating deputies voting networks as well as questions about loyalty, leadership, coalitions, political crisis and polarization.
Section:
Subject Area 3: Graphs and Networks
5. The Problem of Action at a Distance in Networks and the Emergence of Preferential Attachment from Triadic Closure
In this paper, we characterise the notion of preferential attachment in networks as action at a distance, and argue that it can only be an emergent phenomenon – the actual mechanism by which networks grow always being the closing of triangles. After a review of the concepts of triangle closing and preferential attachment, we present our argument, as well as a simplified model in which preferential attachment can be derived mathematically from triangle closing. Additionally, we perform experiments on synthetic graphs to demonstrate the emergence of preferential attachment in graph growth models based only on triangle closing.
Section:
Subject Area 3: Graphs and Networks
6. Analyse de réseaux criminels de traite des êtres humains: méthodologie, modélisation et visualisation
Cet article dessine le contexte d'une étude portant sur les réseaux criminels de traite des êtres humains et décrit la rencontre de trois champs disciplinaires engagés dans ces travaux: Droit, Sociologie et Informatique, ainsi que les éléments méthodologiques développés. Il pose les fondations d'une méthodologie venant en appui à l'étude juridique des réseaux criminels, et plus spécifiquement de ceux se livrant à des faits de traite des êtres humains. La ``science des réseaux'' (Network Science), vue à la fois comme une abstraction mathématique et une approche et méthodologie sociologique, sert de socle pour formuler et explorer un faisceau d'hypothèses éclairant le(s) mode(s) opératoire(s) des réseaux criminels. Les leçons apprises, nourries des interactions entre disciplines, permettent de dessiner les axes de travaux futurs pour améliorer la méthodologie avancée.
Section:
Subject Area 3: Graphs and Networks