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Authors:OWAIS A. HUSSAIN, MAAZ BIN AHMAD, FARAZ A. ZAIDI Abstract: Advances in Complex Systems, Ahead of Print. Among diverse topics in complex network analysis, the idea of extracting a small set of nodes which can maximally influence other nodes in the network has a variety of applications, especially for e-marketing and social networking. While there is an abundance of heuristics to identify such influential nodes, the method of quantifying the influence itself, has not been investigated in the research community. Most of the classical and state-of-the-art works use Diffusion tests for influence benchmark of a particular set of nodes in the network. The underlying study challenges this method and conducts thorough experiments to show that for real-world applications, the diffusion test alone is not only insufficient, but in some cases is also an inaccurate method of benchmarking. Using eight widely adopted heuristics, 25 networks were tested using Diffusion tests and compared with resilience test, we found out that no single algorithm performs consistently on both types of tests. Thus, we conclude that a more accurate way of benchmarking a set of influential nodes is to run diffusion tests alongside resilience test, in order to label a certain technique as best performer. Citation: Advances in Complex Systems PubDate: 2022-12-31T08:00:00Z DOI: 10.1142/S0219525922500102
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Authors:LUIS A. MICCIO, CARLOS GÁMEZ-PÉREZ, JUAN LUIS SUÁREZ, GUSTAVO A. SCHWARTZ Abstract: Advances in Complex Systems, Ahead of Print. To discern the role social and cultural networks play in the emergence of preeminent historical figures and ideas in History, we use a method based on complex networks analysis to reveal emergent interactions in Wikipedia. We built a network constituted by derivative links, where nodes are connected if they are co-linked by other papers or co-link other papers within Wikipedia. We apply this method, focused on the structural distance, to three significant individuals associated with the Italian Renaissance: Copernicus, Michelangelo, and Pico della Mirandola. The results point to the effectiveness of this approach for discovering new knowledge about the interdisciplinary transactions between people and ideas coming from artistic, scientific and philosophical domains during this period. The emergent network reflects the apparently strong network-level interactions between Michelangelo and Mirandola’s clusters; the importance of Hermeticism across the three clusters; and how the so-called “knowledge dealers” related to Neoplatonism contribute to the depiction of the period by future historians. Finally, we advance the notion of “focus reading”, in which complex networks analysis allows us to build bridges between close and distant forms of reading historical evidence. Citation: Advances in Complex Systems PubDate: 2022-11-17T08:00:00Z DOI: 10.1142/S0219525922400100
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Authors:Ramona Roller, Maximilian Schich, Hyejin Youn, Mikhail Tamm Abstract: Advances in Complex Systems, Ahead of Print.
Citation: Advances in Complex Systems PubDate: 2022-11-11T08:00:00Z DOI: 10.1142/S0219525922020027
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Authors:TANYA ARAÚJO, R. VILELA MENDES Abstract: Advances in Complex Systems, Ahead of Print. Long-range connections play an essential role in dynamical processes on networks, on the processing of information in biological networks, on the structure of social and economical networks and in the propagation of opinions and epidemics. Here, we review the evidence for long-range connections in real-world networks and discuss the nature of the nonlocal diffusion arising from different distance-dependent laws. Particular attention is devoted to the characterization of diffusion in finite networks for moderate large times and to the comparison of distance laws of exponential and power type. Citation: Advances in Complex Systems PubDate: 2022-11-09T08:00:00Z DOI: 10.1142/S0219525922500096
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Authors:DMITRY ZINOVIEV Abstract: Advances in Complex Systems, Ahead of Print. More than 4600 non-academic music groups had emerged in the USSR and post-Soviet independent nations during 1960–2015, performing in 275 genres. Some groups became legends and survived for decades, while others vanished and are known now only to the most dedicated music history scholars. To explain and predict success, we built a complex network of the groups and their almost 20,000 members based on performers’ sharing using the data from Wikipedia and Google. We calculated the primary network measures: centralities, degree assortativity, and clustering coefficient — and discovered that they could not accurately predict music group success, but they could distinguish between coarse measures of success, such as which groups were above or below the median. In particular, all centralities positively correlate with success, and the clustering coefficient non-linearly maximizes it. The proposed network-based success exploration and prediction methods are transferable to other arts and humanities areas with medium- or long-term team-based collaborations. Citation: Advances in Complex Systems PubDate: 2022-11-03T07:00:00Z DOI: 10.1142/S0219525922400094
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Authors:MADELEINE JANICKYJ, DANIEL CURLEY, PÁDRAIG MACCARRON, MIKE MCCARTHY, JOSEPH YOSE, RALPH KENNA Abstract: Advances in Complex Systems, Ahead of Print. Táin Bó Cúailnge or the “Cattle Raid of Cooley” (TBC) is the most famous epic narrative in early Irish literature, having been brought to prominence in modern times by Thomas Kinsella’s iconic translation (1969). The origins of TBC were described by Kinsella as “far more ancient” than the medieval manuscripts that relate it and associated prequels to the tale, called remscéla. One of these, not included in Kinsella’s translation, is Táin Bó Fraích — “The raid of Fráoch’s cattle” (TBF). TBF comes in two discontinuous parts which differ in subject matter and style. We examine the structural relationships between TBF as presented by Leahy [Heroic Romances in Ireland (David Nutt, London, 1906)] and TBC from a social networks point of view and compare them with the seven smaller tales presented in Kinsella’s text. We find that network structures in Kinsella’s text — both TBC itself and the remscéla he selected — are similar to those in TBF, and somewhat moreso the first part than the second. Citation: Advances in Complex Systems PubDate: 2022-10-31T07:00:00Z DOI: 10.1142/S0219525922400069
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Authors:MARCO BUONGIORNO NARDELLI, GARLAND CULBRETH, MIGUEL FUENTES Abstract: Advances in Complex Systems, Ahead of Print. We recently introduced the concept of dynamical score network to represent the harmonic progressions in any composition. Through a process of chord slicing, we obtain a representation of the score as a complex network, where every chord is a node and each progression (voice leading) links successive chords. In this paper, we use this representation to extract quantitative information about harmonic complexity from the analysis of the topology of these networks using state-of-the-art statistical mechanics techniques. Since complex networks support the communication of information by encoding the structure of allowed messages, we can quantify the information associated with locating specific addresses through the measure of the entropy of such network. In doing so, we then characterize properties of network topology, such as the degree distribution of a graph or the shortest paths between couples of nodes. Here, we report on two different evaluations of network entropy, diffusion entropy analysis (DEA) and the Kullback–Leibler divergence applied to the conditional degree matrix, and the measurements of complexity they provide, when applied to an extensive corpus of scores spanning 500 years of western classical music. Although the analysis is limited in scope, our results already provide quantitative evidence of an increase of such measures of harmonic complexity over the corpora we have analyzed. Citation: Advances in Complex Systems PubDate: 2022-09-30T07:00:00Z DOI: 10.1142/S0219525922400082
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Authors:PETRO SARKANYCH, NAZAR FEDORAK, YURIJ HOLOVATCH, PÁDRAIG MACCARRON, JOSEPH YOSE, RALPH KENNA Abstract: Advances in Complex Systems, Ahead of Print. In recent times, the advent of network science permitted new quantitative approaches to literary studies. Here, we bring the Kyiv bylyny cycle into the field — East Slavic epic narratives originating in modern-day Ukraine. By comparing them to other prominent European epics, we identify universal and distinguishing properties of the social networks in bylyny. We analyze community structures and rank most important characters. The method allows to bolster hypotheses from humanities literature — such as the position of Prince Volodymyr — and to generate new ones. We show how the Kyiv cycle of bylyny fits very well with narrative networks from other nations — especially heroic ones. We anticipate that, besides delivering new narratological insights, this study will aid future scholars and interested public to navigate their way through Ukraine’s epic story and identify its heroes. Citation: Advances in Complex Systems PubDate: 2022-09-26T07:00:00Z DOI: 10.1142/S0219525922400070
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Authors:VINCENT LABATUT Abstract: Advances in Complex Systems, Ahead of Print. The task of extracting and analyzing character networks from works of fiction, such as novels and movies, has been the object of a number of recent publications. However, only a very few of them focus on graphic novels, and even fewer on European graphic novels. In this paper, we focus on Thorgal, a bande dessinée, i.e. a comic of the French-Belgian tradition. We manually annotate all the volumes of this series, in order to constitute a corpus allowing us to extract its character network. We perform a descriptive analysis of the network structure and compare it to real-world and fictional social networks. We also study the effect of character filtering over the network structure. Finally, we leverage complex network analysis tools to answer two research questions from the literature, related to the similarity between Thorgal and the Saga of Icelanders; and to the position of women in the series. Our data and source code are both publicly available online. Citation: Advances in Complex Systems PubDate: 2022-07-17T07:00:00Z DOI: 10.1142/S0219525922400033
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Authors:JOSHUA BORYCZ, BENJAMIN D. HORNE, R. ALEXANDER BENTLEY Abstract: Advances in Complex Systems, Ahead of Print. Evolutionary studies of cultural complexity often assume that group members select the best information available in the group, effectively diffusing the best innovations, whose advantages are subsequently passed on to the next generation. This would seem to describe the ideal of the scientific process — each cohort of papers in a field surfacing the best innovations, refining them and passing on to the next “layer” or cohort of scientific works. Here, we use academic journal databases to explore this “forking” (branching) process in the evolution of a scientific paradigm. We apply citation network visualization and Latent Dirichlet allocation topic analysis to three different paradigms defined pragmatically as the set of papers citing a highly influential paper in each respective case. Our three case studies indicate a founder effect in how the seminal paper is highly-embedded in the citation network, and yet peripheral to the evolution of topics in subsequent “layers” of publications within the paradigm. This and additional evidence suggest certain topics are selected and followed, while others are left behind. From these case studies we discuss how hitherto undeveloped ideas of the past might be located in the topic space of seminal works of the same fruitful time period. Citation: Advances in Complex Systems PubDate: 2022-07-13T07:00:00Z DOI: 10.1142/S0219525922400045
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