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Flávio L. Pinheiro

Publications and source records attributed to Flávio L. Pinheiro.

14 recordsLinked to original sources

Revealing Process Structure in Urban Mobility Networks

Urban mobility is a multi-entity system that involves travelers, transport modes, and infrastructure. Beyond conventional origin/destination analysis, this paper investigates how process mining can structure and interpret mobility behavior from event data. Using Call Detail Records (CDRs) from Oeiras in the Lisbon metropolitan area (Portugal), we construct both case-centric and object-centric event logs and discover models that summarize flows and typical durations. Results show that most trips are intra-municipal, while inter-municipal flows connect strongly to neighboring areas, with typical inter-parish travel times of about 20 minutes. The object-centric perspective explicitly links trips and transport modes, revealing mode-specific duration differences (e.g., bus vs. car) that inform multimodal planning. Our contributions are: (i) a reproducible pipeline to transform CDRs into process mining artifacts, (ii) empirical evidence that mobility data exhibit a process-like structure, and (iii) the added value of object-centric models for multimodal analysis. Limitations include the low spatial precision of CDRs (tower-sector level) and heuristic transport-mode labels. Future work will integrate transport-network context (e.g., stations and routes) and model object-centric logs as heterogeneous graphs to enable richer and more reliable analysis.

cs.SI↗

Social influence on complex networks as a perturbation to individual behavior

Cooperation is fundamental to the functioning of biological and social systems in both human and animal populations, with the structure of interactions playing a crucial role. Previous studies have used networks to describe interactions and explore the evolution of cooperation, but with limited transposability to social settings due to biologically relevant assumptions. Exogenous processes -- that affect the individual and are not derived from social interactions -- even if unbiased, have a role in supporting cooperation over defection, and this role has been largely overlooked in the context of network-based interactions. Here, we show that selection can favor either cooperation or defection depending on the frequency of exogenous, even if neutral, processes in any population structure. Our framework allows for deriving analytically the conditions for favoring a specific behavior in any network structure strongly affected by non-social environments (frequent exogenous forcing, FEF), which contrasts with previous computationally prohibitive methods. Our results demonstrate that the requirements for favoring cooperation under FEF do not match those in the rare-mutation limit, establishing that underlying neutral processes can be considered a mechanism for cooperation. We reveal that, under FEF, populations are less cooperative, and network heterogeneity can provide an advantage only if targeting specific network properties, clarifying seemingly contradictory experimental results and evolutionary predictions. While focused on cooperation, our assumptions generalize to any decision-making process involving a choice between alternative options. Our framework is particularly applicable to non-homogeneous human populations, offering a new perspective on cooperation science in the context of cultural evolution, where neutral and biased processes within structured interactions are abundant.

physics.soc-ph↗

Taggus: An Automated Pipeline for the Extraction of Characters' Social Networks from Portuguese Fiction Literature

Automatically identifying characters and their interactions from fiction books is, arguably, a complex task that requires pipelines that leverage multiple Natural Language Processing (NLP) methods, such as Named Entity Recognition (NER) and Part-of-speech (POS) tagging. However, these methods are not optimized for the task that leads to the construction of Social Networks of Characters. Indeed, the currently available methods tend to underperform, especially in less-represented languages, due to a lack of manually annotated data for training. Here, we propose a pipeline, which we call Taggus, to extract social networks from literary fiction works in Portuguese. Our results show that compared to readily available State-of-the-Art tools -- off-the-shelf NER tools and Large Language Models (ChatGPT) -- the resulting pipeline, which uses POS tagging and a combination of heuristics, achieves satisfying results with an average F1-Score of $94.1\%$ in the task of identifying characters and solving for co-reference and $75.9\%$ in interaction detection. These represent, respectively, an increase of $50.7\%$ and $22.3\%$ on results achieved by the readily available State-of-the-Art tools. Further steps to improve results are outlined, such as solutions for detecting relationships between characters. Limitations on the size and scope of our testing samples are acknowledged. The Taggus pipeline is publicly available to encourage development in this field for the Portuguese language.2

cs.CL↗

Multi-polarization during the 9th European Parliament

Brexit, a global pandemic, the Russian invasion of Ukraine, and record inflation - few legislative bodies have faced such a cascade of shocks as the European Parliament did during its 9th term (2019-2024). Using the Bipartite Configuration Model and a set of network statistics, this research explores how multi-polarization was characterized during this term by constructing and analyzing co-voting networks across all legislative subjects and within specific legislative subjects. The results contest binary polarization narratives inherited from US/UK scholarship by uncovering a multi-polar landscape. In many legislative subjects, including "Community policies", "Internal market, single market", and "External relations of the Union", coalitions realign fluidly, forming several voting communities rather than a single left-right divide. Ideological affinity and group memberships, not nationality, emerge as the primary forces that bind or separate Members of the European Parliament, reaffirming the chamber's transnational character. Two quantitative patterns stand out. First, the Greens/EFA and The Left display the highest intragroup cohesion, while governing groups - EPP, S&D, and Renew - often fracture into multiple, issue-driven alliances, suggesting declining centrist disciplines. Second, a distinct Eurosceptic versus Euroenthusiastic cleavage crystallizes in matters concerning the "State and evolution of the Union" subject, cutting across economic and social ideologies and hinting at a budding second dimension of parliamentary conflict. This research highlights how legislative consensus in the European Parliament will hinge on navigating a fluid, multi-polar, issue-driven alliance landscape rather than building stable grand coalitions.

physics.soc-ph↗

Heterogeneous Update Processes Shape Information Cascades in Social Networks

A common assumption in the literature on information diffusion is that populations are homogeneous regarding individuals' information acquisition and propagation process: Individuals update their informed and actively communicating state either through imitation (simple contagion) or peer influence (complex contagion). Here, we study the impact of the mixing and placement of individuals with different update processes on how information cascades in social networks. We consider Simple Spreaders, which take information from a random neighbor and communicate it, and Threshold-based Spreaders, which require a threshold number of active neighbors to change their state to active communication. Even though, in a population made exclusively of Simple Spreaders, information reaches all elements of any (connected) network, we show that, when Simple and Threshold-based Spreaders coexist and occupy random positions in a social network, the number of Simple Spreaders systematically amplifies the cascades only in degree heterogeneous networks (exponential and scale-free). In random and modular structures, this cascading effect originated by Simple Spreaders only exists above a critical mass of these individuals. In contrast, when Threshold-based Spreaders are assorted preferentially in the nodes with a higher degree, the cascading effect of Simple Spreaders vanishes, and the spread of information is drastically impaired. Overall, the study highlights the significance of the strategic placement of different roles in networked structures, with Simple Spreaders driving widespread cascades in heterogeneous networks and Threshold-based Spreaders playing a critical regulatory role in information spread with a tunable effect based on the threshold value.

cs.MA↗

How Social Rewiring Preferences Bridge Polarized Communities

Recently, social debates have been marked by increased polarization of social groups. Such polarization not only implies that groups cannot reach a consensus on fundamental questions but also materializes in more modular social spaces/networks that further amplify the risks of polarization in less polarizing topics. How can network adaptation bridge different communities when individuals reveal homophilic or heterophilic social rewiring preferences? Here, we consider information diffusion processes that capture a continuum from simple to complex contagion processes. We use a computational model to understand how fast and to what extent individual rewiring preferences bridge initially weakly connected communities and how likely it is for them to reach a consensus. We show that homophilic and heterophilic rewiring have different impacts depending on the type of opinion spread. First, in the case of complex opinion diffusion, we show that even polarized social networks can reach a population-wide consensus without reshaping their underlying network. When polarized social structures amplify opinion polarization, heterophilic rewiring preferences play a key role in creating bridges between communities and facilitating a population-wide consensus. Secondly, in the case of simple opinion diffusion, homophilic rewiring preferences are more capable of fostering consensus and avoiding a co-existence (dynamical polarization) of opinions. Hence, across a broad profile of simple and complex opinion diffusion processes, only a mix of heterophilic and homophilic rewiring preferences avoids polarization and promotes consensus.

physics.soc-ph↗

Export complexity, industrial complexity and regional economic growth in Brazil

Research on productive structures has shown that economic complexity conditions economic growth. However, little is known about which type of complexity, e.g., export or industrial complexity, matters more for regional economic growth in a large emerging country like Brazil. Brazil exports natural resources and agricultural goods, but a large share of the employment derives from services, non-tradables, and within-country manufacturing trade. Here, we use a large dataset on Brazil's formal labor market, including approximately 100 million workers and 581 industries, to reveal the patterns of export complexity, industrial complexity, and economic growth of 558 micro-regions between 2003 and 2019. Our results show that export complexity is more evenly spread than industrial complexity. Only a few -- mainly developed urban places -- have comparative advantages in sophisticated services. Regressions show that a region's industrial complexity is a significant predictor for 3-year growth prospects, but export complexity is not. Moreover, economic complexity in neighboring regions is significantly associated with economic growth. The results show export complexity does not appropriately depict Brazil's knowledge base and growth opportunities. Instead, promoting the sophistication of the heterogeneous regional industrial structures and development spillovers is a key to growth.

econ.GN↗

Rate-Induced Transitions in Networked Complex Adaptive Systems: Exploring Dynamics and Management Implications Across Ecological, Social, and Socioecological Systems

Complex adaptive systems (CASs), from ecosystems to economies, are open systems and inherently dependent on external conditions. While a system can transition from one state to another based on the magnitude of change in external conditions, the rate of change -- irrespective of magnitude -- may also lead to system state changes due to a phenomenon known as a rate-induced transition (RIT). This study presents a novel framework that captures RITs in CASs through a local model and a network extension where each node contributes to the structural adaptability of others. Our findings reveal how RITs occur at a critical environmental change rate, with lower-degree nodes tipping first due to fewer connections and reduced adaptive capacity. High-degree nodes tip later as their adaptability sources (lower-degree nodes) collapse. This pattern persists across various network structures. Our study calls for an extended perspective when managing CASs, emphasizing the need to focus not only on thresholds of external conditions but also the rate at which those conditions change, particularly in the context of the collapse of surrounding systems that contribute to the focal system's resilience. Our analytical method opens a path to designing management policies that mitigate RIT impacts and enhance resilience in ecological, social, and socioecological systems. These policies could include controlling environmental change rates, fostering system adaptability, implementing adaptive management strategies, and building capacity and knowledge exchange. Our study contributes to the understanding of RIT dynamics and informs effective management strategies for complex adaptive systems in the face of rapid environmental change.

physics.soc-ph↗

Characterization of the Firm-Firm Public Procurement Co-Bidding Network from the State of Ceará (Brazil) Municipalities

Fraud in public funding can have deleterious consequences for the economic, social, and political well-being of societies. Fraudulent activity associated with public procurement contracts accounts for losses of billions of euros every year. Thus, it is of utmost relevance to explore analytical frameworks that can help public authorities identify agents that are more susceptible to incur in irregular activities. Here, we use standard network science methods to study the co-biding relationships between firms that participate in public tenders issued by the $184$ municipalities of the State of Ceará (Brazil) between 2015 and 2019. We identify $22$ groups/communities of firms with similar patterns of procurement activity, defined by their geographic and activity scopes. The profiling of the communities allows us to highlight groups that are more susceptible to market manipulation and irregular activities. Our work reinforces the potential application of network analysis in policy to unfold the complex nature of relationships between market agents in a scenario of scarce data.

physics.soc-ph↗

Scaling Behavior of Public Procurement Activity

Public procurement refers to the purchase by public sector entities, such as government departments or local authorities, of Services, Goods, or Works. It accounts for a significant share of OECD countries' expenditures. However, while governments are expected to execute them as efficiently as possible, there is a lack of methodologies for an adequate comparison of procurement activity between institutions at different scales, which represents a challenge for policymakers and academics. Here, we propose using methods from urban scaling laws literature to study public procurement activity among 278 Portuguese municipalities between 2011 and 2018. We find that public procurement expenditure scales sub-linearly with population size, indicating an economy of scale for public spending as cities increase their population size. Moreover, when looking at the municipal Scale-Adjusted Indicators (the deviations from the scaling laws) by contract type -- Works, Goods, and Services -- we obtain a new local characterization of municipalities based on the similarity of procurement activity. These results make up a framework for quantitatively studying local public expenditure by enabling policymakers a more appropriate ground for comparative analysis.

physics.soc-ph↗

Consensus and Polarisation in Competing Complex Contagion Processes

The rate of adoption of new information depends on reinforcement from multiple sources in a way that often cannot be described by simple contagion processes. In such cases, contagion is said to be complex. Complex contagion happens in the diffusion of human behaviours, innovations, and knowledge. Based on that evidence, we propose a model that considers multiple, potentially asymmetric, and competing contagion processes and analyse its respective population-wide dynamics, bringing together ideas from complex contagion, opinion dynamics, evolutionary game theory, and language competition by shifting the focus from individuals to the properties of the diffusing processes. We show that our model spans a dynamical space in which the population exhibits patterns of consensus, dominance, and, importantly, different types of polarisation, a more diverse dynamical environment that contrasts with single simple contagion processes. We show how these patterns emerge and how different population structures modify them through a natural development of spatial correlations: structured interactions increase the range of the dominance regime by reducing that of dynamic polarisation, tight modular structures can generate structural polarisation, depending on the interplay between fundamental properties of the processes and the modularity of the interaction network.

physics.soc-ph↗

The Higher Education Space, Connecting Degree Programs from Individuals' Choices

Is it possible to derive organizing principles of higher education systems from the applicants' choices? Here we introduce the Higher Education Space (HES) as a way to describe the complex relationship between degree programs. The HES is based on the application of methods from network science to data on the revealed preferences of applicants to the higher education systems of Chile and Portugal. Our work reveals: 1) the existence of a positive assortment of features -- such as gender balance, application scores, unemployment levels, demand-supply ratio, etc -- along the network structure of the HES; 2) that the decaying of the prevalence level of a feature from a focal degree program extends beyond the dyadic relationships captured by the HES; 3) temporal variations in different features do not spillover/propagate throughout the system in the same way; 4) differences in unemployment levels reported among pairs of degree programs are minimized when taking into consideration the connectivity structure of the HES, largely outperforming the differences in matched pairs using traditional similarity measures; and 5) grouping of degree programs based in the network structure of the HES provides an applicant perspective that complements existing classification systems. Our findings support the HES as a multi-dimensional framework that can effectively contribute to the governance of higher education systems.

physics.soc-ph↗

Shooting High or Low: Do Countries Benefit from Entering Unrelated Activities?

Countries tend to diversify their exports by entering products that are related to their current exports. Yet this average behavior is not representative of every diversification path. In this paper, we introduce a method to identify periods when countries enter unrelated products. We analyze the economic diversification paths of 93 countries between 1965 and 2014 and find that countries enter unrelated products in only about 7.2% of all observations. We find that countries enter more unrelated products when they are at an intermediate level of economic development, and when they have higher levels of human capital. Finally, we ask whether countries entering more unrelated products grow faster than those entering only related products. The data shows that countries that enter more unrelated activities experience a small but significant increase in future economic growth, compared to countries with a similar level of income, human capital, capital stock per worker, and economic complexity.

q-fin.GN↗

Local Wealth Redistribution Promotes Cooperation in Multiagent Systems

Designing mechanisms that leverage cooperation between agents has been a long-lasting goal in Multiagent Systems. The task is especially challenging when agents are selfish, lack common goals and face social dilemmas, i.e., situations in which individual interest conflicts with social welfare. Past works explored mechanisms that explain cooperation in biological and social systems, providing important clues for the aim of designing cooperative artificial societies. In particular, several works show that cooperation is able to emerge when specific network structures underlie agents' interactions. Notwithstanding, social dilemmas in which defection is highly tempting still pose challenges concerning the effective sustainability of cooperation. Here we propose a new redistribution mechanism that can be applied in structured populations of agents. Importantly, we show that, when implemented locally (i.e., agents share a fraction of their wealth surplus with their nearest neighbors), redistribution excels in promoting cooperation under regimes where, before, only defection prevailed.

cs.MA↗