arXiv subjects

Janos Kertesz

Publications and source records attributed to Janos Kertesz.

At least 19 recordsLinked to original sources

arXiv2024

Human-AI Coevolution

Human-AI coevolution, defined as a process in which humans and AI algorithms continuously influence each other, increasingly characterises our society, but is understudied in artificial intelligence and complexity science literature. Recommender systems and assistants play a prominent role in human-AI coevolution, as they permeate many facets of daily life and influence human choices on online platforms. The interaction between users and AI results in a potentially endless feedback loop, wherein users' choices generate data to train AI models, which, in turn, shape subsequent user preferences. This human-AI feedback loop has peculiar characteristics compared to traditional human-machine interaction and gives rise to complex and often ``unintended'' social outcomes. This paper introduces Coevolution AI as the cornerstone for a new field of study at the intersection between AI and complexity science focused on the theoretical, empirical, and mathematical investigation of the human-AI feedback loop. In doing so, we: (i) outline the pros and cons of existing methodologies and highlight shortcomings and potential ways for capturing feedback loop mechanisms; (ii) propose a reflection at the intersection between complexity science, AI and society; (iii) provide real-world examples for different human-AI ecosystems; and (iv) illustrate challenges to the creation of such a field of study, conceptualising them at increasing levels of abstraction, i.e., technical, epistemological, legal and socio-political.

cs.AI↗

arXiv2023

A simple model of edit activity in Wikipedia

A simple dynamical model of collective edit activity of Wikipedia articles and their content evolution is introduced. Based on the recent empirical findings, each editor in the model is characterized by an ability to make content edit, i.e., improving the article by adding content and a tendency to make maintenance edit, i.e., dealing with formal aspects and maintaining the edit flow. In addition, each article is characterized by a level of maturity as compared to a potential quality needed to comprehensively cover its topic. This model is found to reproduce the basic structure of the bipartite network between editors and articles of Wikipedia. Furthermore, the relation between the model parameters of editors and articles and the metrics of those calculated from the emergent network turns out to be robust, i.e. depending only on the rate of the introduction of new articles to the editing activity. This results provides us a way to relate observations in the real data to the hidden characteristics of editors and articles. For the nestedness of the networks, systems with weighted parameter distribution gives better match to the empirical one. This suggests the importance of high-dimensional nature of the ability of editors and quality of articles in the real system.

physics.soc-ph↗

arXiv2020

Give more data, awareness and control to individual citizens, and they will help COVID-19 containment

The rapid dynamics of COVID-19 calls for quick and effective tracking of virus transmission chains and early detection of outbreaks, especially in the phase 2 of the pandemic, when lockdown and other restriction measures are progressively withdrawn, in order to avoid or minimize contagion resurgence. For this purpose, contact-tracing apps are being proposed for large scale adoption by many countries. A centralized approach, where data sensed by the app are all sent to a nation-wide server, raises concerns about citizens' privacy and needlessly strong digital surveillance, thus alerting us to the need to minimize personal data collection and avoiding location tracking. We advocate the conceptual advantage of a decentralized approach, where both contact and location data are collected exclusively in individual citizens' "personal data stores", to be shared separately and selectively, voluntarily, only when the citizen has tested positive for COVID-19, and with a privacy preserving level of granularity. This approach better protects the personal sphere of citizens and affords multiple benefits: it allows for detailed information gathering for infected people in a privacy-preserving fashion; and, in turn this enables both contact tracing, and, the early detection of outbreak hotspots on more finely-granulated geographic scale. Our recommendation is two-fold. First to extend existing decentralized architectures with a light touch, in order to manage the collection of location data locally on the device, and allow the user to share spatio-temporal aggregates - if and when they want, for specific aims - with health authorities, for instance. Second, we favour a longer-term pursuit of realizing a Personal Data Store vision, giving users the opportunity to contribute to collective good in the measure they want, enhancing self-awareness, and cultivating collective efforts for rebuilding society.

cs.CY↗

arXiv2017

Peer relations with mobile phone data: Best friends and family formation

Earlier attempts to investigate the changes of the role of friendship in different life stages have failed due to lack of data. We close this gap by using a large data set of mobile phone calls from a European country in 2007, to study how the people's call patterns to their close social contacts are associated with age and gender of the callers. We hypothesize that (i) communication with peers, defined as callers of similar age, will be most important during the period of family formation and that (ii) the importance of best friends defined as same-sex callers of exactly the same age, will be stronger for women than for men. Results show that the frequency of phone calls with the same-sex peers in this population turns out to be relatively stable through life for both men and women. In line with the first hypothesis, there was a significant increase in the length of the phone calls for callers between ages 30 to 40 years. Partly in line with the second hypothesis, the increase in phone calls turned out to be particularly pronounced among females, although there were only minor gender differences in call frequencies. Furthermore, women tended to have long phone conversations with their same-age female friend, and also with somewhat older peers. In sum, we provide evidence from big data for the adult life stages at which peers are most important, and suggest that best friends appear to have a niche of their own in human sociality.

physics.soc-ph↗

arXiv2017

Network of families in a contemporary population: regional and cultural assortativity

Using a large dataset with individual-level demographic information of 60,000 families in contemporary Finland, we analyse the variation and cultural assortativity in a network of families. Families are considered as vertices and unions between males and females who have a common child and belong to different families are considered as edges in such a network of families. The sampled network is a collection of many disjoint components with the largest connected component being dominated by families rooted in one specific region. We characterize the network in terms of the basic structural properties and then explore the network transitivity and assortativity with regards to regions of origin and linguistic identity. Transitivity is seen to result from linguistic homophily in the network. Overall, our results demonstrate that geographic proximity and language strongly influence the structuring of network.

physics.soc-ph↗

arXiv2017

Migration patterns across the life course of families: Gender differences and proximity with parents and siblings in Finland

Family members' life course tendencies to remain geographically close to each other or to migrate due to education or job opportunities have been studied relatively little. Here we investigate migration patterns of parents and their children between 19 administrative regions of Finland from 1970 to 2012. Using the FinnFamily register dataset of 60 000 index individuals and their family members, we investigate the patterns of regional migration and regional co-residence of parents and their children. Specifically, we analyse how likely it is for children to reside in the same region as their parents at any specific age, whether parents and children who live in different regions are likely to reunite, and whether siblings function as regional attractors to each other. Results show an intense regional migration of people to the capital area. The migration propensity of individuals is high in early childhood and peaks in early adulthood. About two thirds of Finnish children live in the same region as their parents throughout their adult lives. Females show higher propensity to migrate than males, since daughters move away from their parents earlier and with a higher rate than sons do. The propensity for two full sibling brothers to be in the same region is higher than that for other types of sibling dyads. We conclude that family members serve as important geographical attractors to each other through the life course and that family attraction is stronger for sons and brothers than for daughters and sisters in contemporary Finland.

physics.soc-ph↗

arXiv2016

Multiplex Modeling of the Society

The society has a multi-layered structure, where the layers represent the different contexts. To model this structure we begin with a single-layer weighted social network (WSN) model showing the Granovetterian structure. We find that when merging such WSN models, a sufficient amount of inter-layer correlation is needed to maintain the relationship between topology and link weights, while these correlations destroy the enhancement in the community overlap due to multiple layers. To resolve this, we devise a geographic multi-layer WSN model, where the indirect inter-layer correlations due to the geographic constraints of individuals enhance the overlaps between the communities and, at the same time, the Granovetterian structure is preserved. Furthermore, the network of social interactions can be considered as a multiplex from another point of view too: each layer corresponds to one communication channel and the aggregate of all them constitutes the entire social network. However, usually one has information only about one of the channels, which should be considered as a sample of the whole. Here we show by simulations and analytical methods that this sampling may lead to bias. For example, while it is expected that the degree distribution of the whole social network has a maximum at a value larger than one, we get with reasonable assumptions about the sampling process a monotonously decreasing distribution as observed in empirical studies of single channel data. We analyse the far-reaching consequences of our findings.

physics.soc-ph↗

arXiv2016

Empirical study of the role of the topology in spreading on communication networks

Topological aspects, like community structure, and temporal activity patterns, like burstiness, have been shown to severly influence the speed of spreading in temporal networks. We study the influence of the topology on the susceptible-infected (SI) spreading on time stamped communication networks, as obtained from a dataset of mobile phone records. We consider city level networks with intra- and inter-city connections. The networks using only intra-city links are usually sparse, where the spreading depends mainly on the average degree. The inter-city links serve as bridges in spreading, speeding up considerably the process. We demonstrate the effect also on model simulations.

cs.SI↗

arXiv2015

Communication with family and friends across the life course

Each stage of the human life course is characterized by a distinctive pattern of social relations. We study how the intensity and importance of the closest social contacts vary across the life course, using a large database of mobile communication from a European country. We first determine the most likely social relationship type from these mobile phone records by relating the age and gender of the caller and recipient to the frequency, length, and direction of calls. We then show how communication patterns between parents and children, romantic partner, and friends vary across the six main stages of the adult family life course. Young adulthood is dominated by a gradual shift of call activity from parents to close friends, and then to a romantic partner, culminating in the period of early family formation during which the focus is on the romantic partner. During middle adulthood call patterns suggest a high dependence on the parents of the ego, who, presumably often provide alloparental care, while at this stage female same-gender friendship also peaks. During post-reproductive adulthood, individuals and especially women balance close social contacts among three generations. The age of grandparenthood brings the children entering adulthood and family formation into the focus, and is associated with a realignment of close social contacts especially among women, while the old age is dominated by dependence on their children.

physics.soc-ph↗

arXiv2015

Kinetics of Social Contagion

Diffusion of information, behavioral patterns or innovations follows diverse pathways depending on a number of conditions, including the structure of the underlying social network, the sensitivity to peer pressure and the influence of media. Here we study analytically and by simulations a general model that incorporates threshold mechanism capturing sensitivity to peer pressure, the effect of `immune' nodes who never adopt, and a perpetual flow of external information. While any constant, non-zero rate of dynamically-introduced spontaneous adopters leads to global spreading, the kinetics by which the asymptotic state is approached shows rich behavior. In particular we find that, as a function of the immune node density, there is a transition from fast to slow spreading governed by entirely different mechanisms. This transition happens below the percolation threshold of network fragmentation, and has its origin in the competition between cascading behavior induced by adopters and blocking due to immune nodes. This change is accompanied by a percolation transition of the induced clusters.

physics.soc-ph↗

arXiv2015

Correlated bursts and the role of memory range

Inhomogeneous temporal processes in natural and social phenomena have been described by bursts that are rapidly occurring events within short time periods alternating with long periods of low activity. In addition to the analysis of heavy-tailed inter-event time distributions, higher-order correlations between inter-event times, called correlated bursts, have been studied only recently. As the possible mechanisms underlying such correlated bursts are far from being fully understood, we devise a simple model for correlated bursts by using a self-exciting point process with variable memory range. Here the probability that a new event occurs is determined by a memory function that is the sum of decaying memories of the past events. In order to incorporate the noise and/or limited memory capacity of systems, we apply two memory loss mechanisms, namely either fixed number or variable number of memories. By using theoretical analysis and numerical simulations we find that excessive amount of memory effect may lead to a Poissonian process, which implies that for memory effect there exists an intermediate range that will generate correlated bursts of magnitude comparable to empirical findings. Hence our results provide deeper understanding of how long-range memory affects correlated bursts.

physics.soc-ph↗

arXiv2012

Challenges in Complex Systems Science

FuturICT foundations are social science, complex systems science, and ICT. The main concerns and challenges in the science of complex systems in the context of FuturICT are laid out in this paper with special emphasis on the Complex Systems route to Social Sciences. This include complex systems having: many heterogeneous interacting parts; multiple scales; complicated transition laws; unexpected or unpredicted emergence; sensitive dependence on initial conditions; path-dependent dynamics; networked hierarchical connectivities; interaction of autonomous agents; self-organisation; non-equilibrium dynamics; combinatorial explosion; adaptivity to changing environments; co-evolving subsystems; ill-defined boundaries; and multilevel dynamics. In this context, science is seen as the process of abstracting the dynamics of systems from data. This presents many challenges including: data gathering by large-scale experiment, participatory sensing and social computation, managing huge distributed dynamic and heterogeneous databases; moving from data to dynamical models, going beyond correlations to cause-effect relationships, understanding the relationship between simple and comprehensive models with appropriate choices of variables, ensemble modeling and data assimilation, modeling systems of systems of systems with many levels between micro and macro; and formulating new approaches to prediction, forecasting, and risk, especially in systems that can reflect on and change their behaviour in response to predictions, and systems whose apparently predictable behaviour is disrupted by apparently unpredictable rare or extreme events. These challenges are part of the FuturICT agenda.

nlin.AO↗

arXiv2011

Communities and beyond: mesoscopic analysis of a large social network with complementary methods

Community detection methods have so far been tested mostly on small empirical networks and on synthetic benchmarks. Much less is known about their performance on large real-world networks, which nonetheless are a significant target for application. We analyze the performance of three state-of-the-art community detection methods by using them to identify communities in a large social network constructed from mobile phone call records. We find that all methods detect communities that are meaningful in some respects but fall short in others, and that there often is a hierarchical relationship between communities detected by different methods. Our results suggest that community detection methods could be useful in studying the general mesoscale structure of networks, as opposed to only trying to identify dense structures.

physics.soc-ph↗

arXiv2011

Extent of force indeterminacy in packings of frictional rigid disks

Static packings of frictional rigid particles are investigated by means of discrete element simulations. We explore the ensemble of allowed force realizations in the space of contact forces for a given packing structure. We estimate the extent of force indeterminacy with different methods. The indeterminacy exhibits a nonmonotonic dependence on the interparticle friction coefficient. We verify directly that larger force-indeterminacy is accompanied by a more robust behavior against local perturbations. We also investigate the local indeterminacy of individual contact forces. The probability distribution of local indeterminacy changes its shape depending on friction. We find that local indeterminacy tends to be larger on force chains for intermediate friction. This correlation disappears in the large friction limit.

cond-mat.soft↗

arXiv2011

Generation of homogeneous granular packings: Contact dynamics method with coupling to an external pressure bath

The contact dynamics method (CD) is an efficient simulation technique of dense granular media where unilateral and frictional contact problems for a large number of rigid bodies have to be solved. In this paper we present a modified version of the contact dynamics to generate homogeneous random packings of rigid grains. CD is coupled to an external pressure bath, which allows the variation of the size of a periodically repeated cell. We follow the concept of the Andersen dynamics and show how it can be applied within the framework of the contact dynamics method. The main challenge here is to handle the interparticle interactions properly, which are based on constraint forces in CD. We implement the proposed algorithm, perform test simulations and investigate the properties of the final packings.

physics.comp-ph↗

arXiv2010

Order flow dynamics around extreme price changes on an emerging stock market

We study the dynamics of order flows around large intraday price changes using ultra-high-frequency data from the Shenzhen Stock Exchange. We find a significant reversal of price for both intraday price decreases and increases with a permanent price impact. The volatility, the volume of different types of orders, the bid-ask spread, and the volume imbalance increase before the extreme events and decay slowly as a power law, which forms a well-established peak. The volume of buy market orders increases faster and the corresponding peak appears earlier than for sell market orders around positive events, while the volume peak of sell market orders leads buy market orders in the magnitude and time around negative events. When orders are divided into four groups according to their aggressiveness, we find that the behaviors of order volume and order number are similar, except for buy limit orders and canceled orders that the peak of order number postpones two minutes later after the peak of order volume, implying that investors placing large orders are more informed and play a central role in large price fluctuations. We also study the relative rates of different types of orders and find differences in the dynamics of relative rates between buy orders and sell orders and between individual investors and institutional investors. There is evidence showing that institutions behave very differently from individuals and that they have more aggressive strategies. Combing these findings, we conclude that institutional investors are more informed and play a more influential role in driving large price fluctuations.

q-fin.TR↗

arXiv2009

Studies of the limit order book around large price changes

We study the dynamics of the limit order book of liquid stocks after experiencing large intra-day price changes. In the data we find large variations in several microscopical measures, e.g., the volatility the bid-ask spread, the bid-ask imbalance, the number of queuing limit orders, the activity (number and volume) of limit orders placed and canceled, etc. The relaxation of the quantities is generally very slow that can be described by a power law of exponent $\approx0.4$. We introduce a numerical model in order to understand the empirical results better. We find that with a zero intelligence deposition model of the order flow the empirical results can be reproduced qualitatively. This suggests that the slow relaxations might not be results of agents' strategic behaviour. Studying the difference between the exponents found empirically and numerically helps us to better identify the role of strategic behaviour in the phenomena.

q-fin.TR↗

arXiv2009

Detecting the overlapping and hierarchical community structure of complex networks

Many networks in nature, society and technology are characterized by a mesoscopic level of organization, with groups of nodes forming tightly connected units, called communities or modules, that are only weakly linked to each other. Uncovering this community structure is one of the most important problems in the field of complex networks. Networks often show a hierarchical organization, with communities embedded within other communities; moreover, nodes can be shared between different communities. Here we present the first algorithm that finds both overlapping communities and the hierarchical structure. The method is based on the local optimization of a fitness function. Community structure is revealed by peaks in the fitness histogram. The resolution can be tuned by a parameter enabling to investigate different hierarchical levels of organization. Tests on real and artificial networks give excellent results.

physics.soc-ph↗