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Journal articleGoto H, Viegas E, Takayasu H, et al., 2019,
Dynamics of essential interaction between firms on financial reports
, PLoS One, Vol: 14, Pages: 1-16, ISSN: 1932-6203Companies tend to publish financial reports in order to articulate strategies, disclose key performance measurements as well as summarise the complex relationships with external stakeholders as a result of their business activities. Therefore, any major changes to business models or key relationships will be naturally reflected within these documents, albeit in an unstructured manner. In this research, we automatically scan through a large and rich database, containing over 400,000 reports of companies in Japan, in order to generate structured sets of data that capture the essential features, interactions and resulting relationships among these firms. In doing so, we generate a citation type network where we empirically observe that node creation, annihilation and link rewiring to be the dominant processes driving its structure and formation. These processes prompt the network to rapidly evolve, with over a quarter of the interactions between firms being altered within every single calendar year. In order to confirm our empirical observations and to highlight and replicate the essential dynamics of each of the three processes separately, we borrow inspiration from ecosystems and evolutionary theory. Specifically, we construct a network evolutionary model where we adapt and incorporate the concept of fitness within our numerical analysis to be a proxy real measure of a company’s importance. By making use of parameters estimated from the real data, we find that our model reliably replicates degree distributions and motif formations of the citation network, and therefore reproducing both macro as well as micro, local level, structural features. This is done with the exception of the real frequency of bidirectional links, which are primarily formed as a result of an entirely separate and distinct process, namely the equity investments from one company into another.
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Journal articleRajpal H, Rosas De Andraca FE, Jensen HJ, 2019,
Tangled worldview model of opinion dynamics
, Frontiers in Physics, Vol: 7, ISSN: 2296-424XWe study the joint evolution of worldviews by proposing a model of opinion dynamics, which is inspired in notions fromevolutionary ecology. Agents update their opinion on a specific issue based on their propensity to change – asserted by thesocial neighbours – weighted by their mutual similarity on other issues. Agents are, therefore, more influenced by neighbourswith similar worldviews (set of opinions on various issues), resulting in a complex co-evolution of each opinion. Simulationsshow that the worldview evolution exhibits events of intermittent polarization when the social network is scale-free. This, in turn,triggers extreme crashes and surges in the popularity of various opinions. Using the proposed model, we highlight the role ofnetwork structure, bounded rationality of agents, and the role of key influential agents in causing polarization and intermittentreformation of worldviews on scale-free networks.
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Journal articleCofré R, Herzog R, Corcoran D, et al., 2019,
A comparison of the maximum entropy principle across biological spatial scales
, Entropy: international and interdisciplinary journal of entropy and information studies, Vol: 21, Pages: 1-20, ISSN: 1099-4300Despite their differences, biological systems at different spatial scales tend to exhibit common organizational patterns. Unfortunately, these commonalities are often hard to grasp due to the highly specialized nature of modern science and the parcelled terminology employed by various scientific sub-disciplines. To explore these common organizational features, this paper provides a comparative study of diverse applications of the maximum entropy principle, which has found many uses at different biological spatial scales ranging from amino acids up to societies. By presenting these studies under a common approach and language, this paper aims to establish a unified view over these seemingly highly heterogeneous scenarios.
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Journal articleCofré R, Videla L, Rosas F, 2019,
An introduction to the non-equilibrium steady states of maximum entropy spike trains
, Entropy, Vol: 21, Pages: 1-28, ISSN: 1099-4300Although most biological processes are characterized by a strong temporal asymmetry, several popular mathematical models neglect this issue. Maximum entropy methods provide a principled way of addressing time irreversibility, which leverages powerful results and ideas from the literature of non-equilibrium statistical mechanics. This tutorial provides a comprehensive overview of these issues, with a focus in the case of spike train statistics. We provide a detailed account of the mathematical foundations and work out examples to illustrate the key concepts and results from non-equilibrium statistical mechanics.
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Journal articleRosas FE, Mediano PAM, Gastpar M, et al., 2019,
Quantifying high-order interdependencies via multivariate extensions of the mutual information
, Physical Review E, Vol: 100, ISSN: 2470-0045This paper introduces a model-agnostic approach to study statistical synergy, a form of emergence in which patterns at large scales are not traceable from lower scales. Our framework leverages various multivariate extensions of Shannon's mutual information, and introduces the O-information as a metric that is capable of characterizing synergy- and redundancy-dominated systems. The O-information is a symmetric quantity, and can assess intrinsic properties of a system without dividing its parts into “predictors” and “targets.” We develop key analytical properties of the O-information, and study how it relates to other metrics of high-order interactions from the statistical mechanics and neuroscience literature. Finally, as a proof of concept, we present an exploration on the relevance of statistical synergy in Baroque music scores.
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Journal articleYao Q, Evans TS, Christensen K, 2019,
How the network properties of shareholders vary with investor type and country
, PLoS One, Vol: 14, Pages: 1-19, ISSN: 1932-6203We construct two examples of shareholder networks in which shareholders are connected if they have shares in the same company. We do this for the shareholders in Turkish companies and we compare this against the network formed from the shareholdings in Dutch companies. We analyse the properties of these two networks in terms of the different types of shareholder. We create a suitable randomised version of these networks to enable us to find significant features in our networks. For that we find the roles played by different types of shareholder in these networks, and also show how these roles differ in the two countries we study.
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Journal articleViegas EM, Goto H, Takayasu H, et al., 2019,
Assembling real networks from synthetic and unstructured subsets: the corporate reporting case
, Scientific Reports, Vol: 9, ISSN: 2045-2322The analysis of interfirm business transaction networks provides invaluable insight into the trading dynamics and economicstructure of countries. However, there is a general scarcity of data available recording real, accurate and extensive informationfor these types of networks. As a result, and in common with other types of network studies - such as protein interactions forinstance - research tends to rely on partial and incomplete datasets, i.e. subsets, with less certain conclusions. Hereh, wemake use of unstructured financial and corporate reporting data in Japan as the base source to construct a financial reportingnetwork, which is then compared and contrasted to the wider real business transaction network. The comparative analysisbetween these two rich datasets - the proxy, partially derived network and the real, complete network at macro as well as localstructural levels - provides an enhanced understanding of the non trivial relationships between partial sampled subsets andfully formed networks. Furthermore, we present an elemental agent based pruning algorithm that reconciles and preserves keystructural differences between these two networks, which may serve as an embryonic generic framework of potentially wideruse to network research, enabling enhanced extrapolation of conclusions from partial data or subsets.
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Journal articleCofre R, Herzog R, Corcoran D, et al., 2019,
A comparison of the maximum entropy principle across biological spatial scales
Despite their obvious differences, biological systems at different scales tend to exhibit common organizational patterns. Unfortunately, these commonalities are usually obscured by the parcelled terminology employed by various scientific sub-disciplines. To explore these commonalities, this papers a comparative study of diverse applications of the maximum entropy principle, ranging from amino acids up to societies. By presenting these studies under a common language, this paper establishes a unified view over seemingly highly heterogeneous biological scenarios.
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Journal articleAzari MM, Rosas F, Pollin S, 2019,
Cellular connectivity for UAVs: Network modeling, performance analysis, and design guidelines
, IEEE Transactions on Wireless Communications, Vol: 18, Pages: 3366-3381, ISSN: 1536-1276The growing use of aerial user equipments (UEs) in various applications requires ubiquitous and reliable connectivity for safe control and data exchange between these devices and ground stations. Key questions that need to be addressed when planning the deployment of aerial UEs are whether the cellular network is a suitable candidate for enabling such connectivity and how the inclusion of aerial UEs might impact the overall network efficiency. This paper provides an in-depth analysis of user and network-level performance of a cellular network that serves both unmanned aerial vehicles (UAVs) and ground users in the downlink. Our results show that the favorable propagation conditions that UAVs enjoy due to their height often backfire on them, as the increased load-dependent co-channel interference received from neighboring ground base stations (BSs) is not compensated by the improved signal strength. When compared with a ground user in an urban area, our analysis shows that a UAV flying at 100 m can experience a throughput decrease of a factor 10 and a coverage drop from 76% to 30%. Motivated by these findings, we develop UAV and network-based solutions to enable an adequate integration of UAVs into cellular networks. In particular, we show that an optimal tilting of the UAV antenna can increase the coverage from 23% to 89% and throughput from 3.5 to 5.8 b/s/Hz, outperforming ground UEs. Furthermore, our findings reveal that depending on the UAV altitude and its antenna configuration, the aerial user performance can scale with respect to the network density better than that of a ground user. Finally, our results show that network densification and the use of microcells limit the UAV performance. Although UAV usage has the potential to increase the area spectral efficiency (ASE) of cellular networks with a moderate number of cells, they might hamper the development of future ultradense networks.
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Journal articleRosas De Andraca FE, Faggian M, Ginelli F, et al., 2019,
Synchronization in time-varying random networks with vanishing connectivity
, Scientific Reports, Vol: 9, Pages: 1-11, ISSN: 2045-2322A sufficiently connected topology linking the constituent units of a complex system is usually seen as a prerequisite forthe emergence of collective phenomena such as synchronization. We present a random network of heterogeneous phaseoscillators in which the links mediating the interactions are constantly rearranged with a characteristic timescale and, possibly,an extremely low instantaneous connectivity. We show that with strong coupling and sufficiently fast rewiring the networkreaches partial synchronization even in the vanishing connectivity limit. In particular, we provide an approximate analyticalargument, based on the comparison between the different characteristic timescales of our system in the low connectivityregime, which is able to predict the transition to synchronization threshold with satisfactory precision beyond the formal fastrewiring limit. We interpret our results as a qualitative mechanism for emergence of consensus in social communities. Inparticular, our result suggest that groups of individuals are capable of aligning their opinions under extremely sparse exchangesof views, which is reminiscent of fast communications that take place in the modern social media. Our results may also berelevant to characterize the onset of collective behavior in engineered systems of mobile units with limited wireless capabilities
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