arXiv subjects

Yérali Gandica

Publications and source records attributed to Yérali Gandica.

15 recordsLinked to original sources

arXiv2026

Temporal patterns of preferences through Wikipedia editing in different languages

Temporal editing patterns on Wikipedia provide a computational lens on cultural dynamics across linguistic communities. We analyse a decade of editorial activity (2001--2010) in eleven Wikipedia language editions and apply hierarchical clustering to two representations of collective behaviour: a static one, based on the thematic composition of each edition, and a temporal one, based on its weekly activity cycle within each thematic category. For the temporal representation we compare two normalisations: one retains only the shape of the weekly cycle, and the other combines it with thematic composition. The linguistic communities exhibit distinct circadian and weekly editing rhythms. Some groupings are recovered by both representations and by both activity metrics (edits and editors), most notably Russian and Chinese, whereas others, such as German and French, emerge only from temporal activity rhythms. Temporal information thus reveals structure that thematic composition alone does not, which points to time as a relevant and often neglected dimension in cross-cultural analyses of digital trace data, and in studies that use online platforms as proxies for collective cultural behaviour.

physics.soc-ph↗

arXiv2026

Self-Similarity in Online Networks During Social Movements

Online platforms provide an infrastructure for social movements, leaving digital traces that can be modelled as networks to quantify how information, participation, and coordination emerge during episodes of collective action and evolve over time. In this work, we unveil the emergence of scale-invariant online interaction patterns in social movements through network analysis of three geographically and sociopolitically distinct massive mobilisation events. By constructing co-occurrence networks from Twitter (now X) hashtag data and applying a degree-thresholding renormalisation procedure, we demonstrate that these highly correlated social phenomena exhibit clear signatures of self-similarity at peak mobilisation times. These critical points are characterised by modular-to-nested transitions, both in the co-occurrence networks and the bi-partite ones, maxima in user participation, and clustering spectrum collapse across multiple network scales. Despite their geographical and sociopolitical diversity, all three movements display remarkably analogous self-similar properties. Furthermore, the results hint at the emergence of a latent metric structure that supports successful hyperbolic embedding, providing an estimate of effective social distance. Together, these findings suggest that self-similarity may constitute a universal organising principle of social movements during peak mobilisation phases, as it lays the groundwork for the rapid amplification of information across scales that is necessary for the successful coordination of collective action.

physics.soc-ph↗

arXiv2024

An entropic analisis of social demonstrations

Social media has dramatically influenced how individuals and groups express their demands, concerns and aspirations during social demonstrations. The study of X or Twitter hashtags during those events has revealed the presence of some temporal points characterised by high correlation among their participants. It has also been reported that the connectivity presents a modular-to-nested transition at the point of maximum correlation. The present study aims to determine whether it is possible to characterise this transition using entropic-based tools. Our results show that entropic analysis can effectively find the transition point to the nested structure, allowing researchers to know that the transition occurs without the need for a network representation. The entropic analysis also shows that the modular-to-nested transition is characterised not by the diversity in the number of hashtags users post but by how many hashtags they share.

physics.soc-ph↗

arXiv2024

Bounded confidence model on growing populations

This paper studies the bounded confidence model on growing fully-mixed populations. In this model, in addition to the usual opinion clusters, significant secondary clusters of smaller size appear systematically, while those secondary clusters appear erratically and include much fewer agents when the population is fixed. Through simulations, we derive the bifurcation diagram of the growing population model and compare it to the diagram obtained with an evolving probability density instead of agents, and with their equivalent with a fixed population. Our tests when changing the usual bounded confidence function into a smooth bounded confidence function suggest that these secondary clusters are mainly generated by a different mechanism when the population is growing than when it is fixed.

physics.soc-ph↗

arXiv2024

Signs of criticality in social explosions

The success of an on-line movement could be defined in terms of the shift to large-scale and the later off-line massive street actions of protests. The role of social media in this process is to facilitate the transformation from small or local feelings of disagreement into large-scale social actions. The way how social media achieves that effect is by growing clusters of people and groups with similar effervescent feelings, which in another case would never be in communication. It is natural to think that these kinds of macro social actions, as a consequence of the spontaneous and massive interactions, will attain the growth and divergence of the correlation length, giving rise to important simplifications on several statistics. In this work, we report the presence of signs of criticality in social demonstrations. Namely, the same power-law exponents are found whenever the distributions are calculated, either considering the same windows-time or the same number of hashtags. The exponents for the distributions during the event were found to be smaller than before (and after) the event. The latter also happens whenever the hashtags are counted only once per user or if all their usages are considered. By means of network representations, we show that the systems present two kinds of high correlations, characterised by either high or low values of modularity. The temporal points of high modularity are characterised by a sustained correlation while the ones of low modularity are characterised by a punctual correlation. The importance of analysing systems near a critical point is that any small disturbance can escalate and induce large-scale -- nationwide -- chain reactions.

physics.soc-ph↗

arXiv2022

The Detection and effect of social events on Wikipedia data-set for studying human preferences

Several studies have used Wikipedia (WP) data-set to analyse worldwide human preferences by languages. However, those studies could suffer from bias related to exceptional social circumstances. Any massive event promoting the exceptional edition of WP can be defined as a source of bias. In this article, we follow a procedure for detecting outliers. Our study is based on $12$ languages and $13$ different categories. Our methodology defines a parameter, which is language-depending instead of being externally fixed. We also study the presence of human cyclic behaviour to evaluate apparent outliers. After our analysis, we found that the outliers in our data set do not significantly affect using the whole Wikipedia-data set as a digital footprint to analyse worldwide human preferences.

physics.soc-ph↗

arXiv2021

Bali's ancient rice terraces: A Hamiltonian approach

We propose a Hamiltonian approach to reproduce the relevant elements of the centuries-old Subak irrigation system in Bali, showing a cluster-size power-law distribution. The resulting system presents two equilibria. The first balance is between energy and entropy contributions. The second lies in the energy contribution: a local Potts-type interaction and a long-range anti-ferromagnetic one without attenuation. Finite-size scaling analysis shows that as a result of the second balance, the transition balancing energy and entropy contributions for low values of the antiferromagnetic contribution is absorbed by the transition for high values of that contribution as the system size increases. The system thus presents only a weak-first order phase transition at the thermodynamic limit. This extends the Hamiltonian framework to a new domain of coupled human-environmental interactions.

cond-mat.stat-mech↗

arXiv2021

The consequences of hesitation: Axelrod model with intrinsic noise

We study the influence of hesitating agents in the Axelrod model by introducing an intrinsic noise, which is proportional to the disagreement between the interacting agents, and thus coupled to the dynamics. Our results show that, unlike the effect of the cultural drift where the noise is just controlled by an external parameter, the intrinsic noise never allows the system to reach a frozen state in the thermodynamic limit. Moreover, we show that when the intrinsic noise affects the agents' variables, the system's behaviour is also different from the case when it affects the network of their interactions.

physics.soc-ph↗

arXiv2020

Measuring the effect of node aggregation on community detection

Many times the nodes of a complex network, whether deliberately or not, are aggregated for technical, ethical, legal limitations or privacy reasons. A common example is the geographic position: one may uncover communities in a network of places, or of individuals identified with their typical geographical position, and then aggregate these places into larger entities, such as municipalities, thus obtaining another network. The communities found in the networks obtained at various levels of aggregation may exhibit various degrees of similarity, from full alignment to perfect independence. This is akin to the problem of ecological and atomic fallacies in statistics, or to the Modified Areal Unit Problem in geography. We identify the class of community detection algorithms most suitable to cope with node aggregation, and develop an index for aggregability, capturing to which extent the aggregation preserves the community structure. We illustrate its relevance on real-world examples (mobile phone and Twitter reply-to networks). Our main message is that any node-partitioning analysis performed on aggregated networks should be interpreted with caution, as the outcome may be strongly influenced by the level of the aggregation.

physics.soc-ph↗

arXiv2020

The free and freer XY models

We study two versions of the XY model where the spins but also the interaction topology is allowed to change. In the free XY model, the number of links is fixed, but their positions in the network are not. We also study a more relaxed version where even the number of links is allowed to vary, we call it the freer XY model. When the interaction networks are dense enough, both models have phase transitions visible both in spin configurations and the network structure. The low-temperature phase in the free XY model, is characterized by tightly connected clusters of spins pointing in the same direction, and isolated spins disconnected from the rest. For the freer XY model the low-temperature phase is almost completely connected. In both models, exponents describing the magnetic ordering are mostly consistent with values of the mean-field theory of the standard XY model.

physics.comp-ph↗

arXiv2019

A multilevel analysis to systemic exposure: insights from local and system-wide information

In the aftermath of the financial crisis, the growing literature on financial networks has widely documented the predictive power of topological characteristics (e.g. degree centrality measures) to explain the systemic impact or systemic vulnerability of financial institutions. In this work, we show that considering alternative topological measures based on local sub-network environment improves our ability to identify systemic institutions. To provide empirical evidence, we apply a two-step procedure. First, we recover network communities (i.e. close-peer environment) on a spillover network of financial institutions. Second, we regress alternative measures of vulnerability on three levels of topological measures: the global level (i.e. firm topological characteristics computed over the whole system), local level (i.e. firm topological characteristics computed over the community) and aggregated level by averaging individual characteristics over the community. The sample includes $46$ financial institutions (banks, broker-dealers, insurance and real-estate companies) listed in the Standard \& Poor's 500 index. Our results confirm the informational content of topological metrics based on close-peer environment. Such information is different from the one embeds in traditional system wide topological metrics and is proved to be predictor of distress for financial institutions in time of crisis.

q-fin.GN↗

arXiv2018

Population preferences through Wikipedia edits

In this work, we are interested in the inner-cultural background shaping broad people's preferences. Our interest is also to track this human footprint, as it has the tendency to disappear due to the nowadays globalization. Given that language is a social construction, it is part of the historical reservoir, shaping the cultural (and hence collective) identity, then helping the community to archive accumulated knowledge about its culture and identity. We assume that the collective interest of a language-speaking community to document their events, people and any feature important for them, by the online encyclopedia Wikipedia, can act as a footprint of the whole group's collective identity. The analysis of the language's preferences into categories among several languages, could have also applications into the field of Multilingual Natural Language Processing (MNLP). We, then, report results about the number of edits, editors, and pages into categories, displayed by the several languages. Results are shown by several angles, and some extra measures complement the analysis.

physics.soc-ph↗

arXiv2018

Fragmentation, integration and macroprudential surveillance of the US financial industry: Insights from network science

Drawing on recent contributions inferring financial interconnectedness from market data, our paper provides new insights on the evolution of the US financial industry over a long period of time by using several tools coming from network science. Following [1] a Time-Varying Parameter Vector AutoRegressive (TVP-VAR) approach on stock market returns to retrieve unobserved directed links among financial institutions, we reconstruct a fully dynamic network in the sense that connections are let to evolve through time. The financial system analysed consists of a large set of $155$ financial institutions that are all the banks, broker-dealers, insurance and real estate companies listed in the Standard & Poor's $500$ index over the period $1993 - 2014$. Looking alternatively at the individual, then sector-, community- and system-wide levels, we show that network science's tools are able to support well known features of the financial markets such as the dramatic fall of connectivity following Lehman Brothers' collapse. More importantly, by means of less traditional metrics, such as sectoral interface or measurements based on contagion processes, our results document the co-existence of both fragmentation and integration phases between firms independently from the sector they belong to, and in doing so, question the relevance of existing macroprudential surveillance frameworks which have been mostly developed on a sectoral basis. Overall, our results improve our understanding of the US financial landscape and may have important implications for risk monitoring as well as macroprudential policy design.

physics.soc-ph↗

arXiv2011

Cluster size entropy in the Axelrod model of social influence: small-world networks and mass media

We study the Axelrod's cultural adaptation model using the concept of cluster size entropy, $S_{c}$ that gives information on the variability of the cultural cluster size present in the system. Using networks of different topologies, from regular to random, we find that the critical point of the well-known nonequilibrium monocultural-multicultural (order-disorder) transition of the Axelrod model is unambiguously given by the maximum of the $S_{c}(q)$ distributions. The width of the cluster entropy distributions can be used to qualitatively determine whether the transition is first- or second-order. By scaling the cluster entropy distributions we were able to obtain a relationship between the critical cultural trait $q_c$ and the number $F$ of cultural features in regular networks. We also analyze the effect of the mass media (external field) on social systems within the Axelrod model in a square network. We find a new partially ordered phase whose largest cultural cluster is not aligned with the external field, in contrast with a recent suggestion that this type of phase cannot be formed in regular networks. We draw a new $q-B$ phase diagram for the Axelrod model in regular networks.

physics.soc-ph↗

arXiv2010

Continuous opinion model in small world directed networks

In the compromise model of continuous opinions proposed by Deffuant et al, the states of two agents in a network can start to converge if they are neighbors and if their opinions are sufficiently close to each other, below a given threshold of tolerance $ε$. In directed networks, if agent i is a neighbor of agent j, j need not be a neighbor of i. In Watts-Strogatz networks we performed simulations to find the averaged number of final opinions $ $ and their distribution as a function of $ε$ and of the network structural disorder. In directed networks $ $ exhibits a rich structure, being larger than in undirected networks for higher values of $ε$, and smaller for lower values of $ε$.

physics.soc-ph↗