Papers by Francesca Colaiori
C rackling noise is a common feature in many dynamic systems 1-9 , the most familiar instance of ... more C rackling noise is a common feature in many dynamic systems 1-9 , the most familiar instance of which is the sound made by a sheet of paper when crumpled into a ball. Although seemingly random, this noise contains fundamental information about the properties of the system in which it occurs. One potential source of such information lies in the asymmetric shape of noise pulses emitted by a diverse range of noisy systems Crackling noise is the response of many physical systems to a slow external driving force, characterized by outbursts of activity (avalanches or pulses) spanning a broad range of sizes, separated by quiescent intervals 1 . In condensed matter, notable examples are the magnetization noise emitted along the hysteresis loop in ferromagnets (that is, the Barkhausen effect 2 ), the noise from magnetic vortices in type-II superconductors 3
The evolutionary dynamics of human Influenza A virus presents a challenging theoretical problem. ... more The evolutionary dynamics of human Influenza A virus presents a challenging theoretical problem. An extremely high mutation rate allows the virus to escape, at each epidemic season, the host immune protection elicited by previous infections. At the same time, at each given epidemic season a single quasi-species, that is a set of closely related strains, is observed. A non-trivial relation between the genetic (i.e., at the sequence level) and the antigenic (i.e., related to the host immune response) distances can shed light into this puzzle. In this paper we introduce a model in which, in accordance with experimental observations, a simple interaction rule based on spatial correlations among point mutations dynamically defines an immunity space in the space of sequences. We investigate the static and dynamic structure of this space and we discuss how it affects the dynamics of the virus-host interaction. Interestingly we observe a staggered time structure in the virus evolution as in the real Influenza evolutionary dynamics.
Abstract. We develop an algorithm to detect community structure in complex networks. The algorith... more Abstract. We develop an algorithm to detect community structure in complex networks. The algorithm is based on spectral methods and takes into account weights and links orientations. Since the method detects efficiently clustered nodes in large networks even when these are not sharply partitioned, it turns to be specially suitable to the analysis of social and information networks. We test the algorithm on a large-scale data-set from a psychological experiment of word association. In this case, it proves to be successful both in clustering words, and in uncovering mental association patterns. 1 Communities in Networks Complex networks are composed by a large number of elements (nodes), organized into sub-communities summing up to form the whole system. The partition of a complex network has no unique solution, since nodes can be aggregated according to different criteria. However, when dealing with networks an additional constraint bounds the possible choices: the entire information...
Cross-immunity plays a crucial role in the epidemiological properties of influenza A virus. Recen... more Cross-immunity plays a crucial role in the epidemiological properties of influenza A virus. Recent experimental studies have pointed out that genetic distances do not fully account for the observed antigenic clusters. In particular, jumps from an antigenic cluster to another seem to be triggered by correlated mutations. However, no specific sites determine whether a sequence belongs to a given antigenic cluster, suggesting that sites mutations could be dynamically correlated. In this paper we introduce an epistatic interaction rule among mutations that dynamically defines neutral clusters in the immunity space. We investigate the structure of this epistatic immunity space, highlighting how this can affect the dynamical properties of the virus-host interaction.
Human languages are rule governed, but almost invariably these rules have exceptions in the form ... more Human languages are rule governed, but almost invariably these rules have exceptions in the form of irregularities. Since rules in language are efficient and productive, the persistence of irregularity is an anomaly. How does irregularity linger in the face of internal (endogenous) and external (exogenous) pressures to conform to a rule? Here we address this problem by taking a detailed look at simple past tense verbs in the Corpus of Historical American English. The data show that the language is open, with many new verbs entering. At the same time, existing verbs might tend to regularize or irregularize as a consequence of internal dynamics, but overall, the amount of irregularity sustained by the language stays roughly constant over time. Despite continuous vocabulary growth, and presumably, an attendant increase in expressive power, there is no corresponding growth in irregularity. We analyze the set of irregulars, showing they may adhere to a set of minority rules, allowing for increased stability of irregularity over time. These findings contribute to the debate on how language systems become rule governed, and how and why they sustain exceptions to rules, providing insight into the interplay between the emergence and maintenance of rules and exceptions in language.
Tracking Language Evolution as an Interdisciplinary, Cross-Theoretical Enterprise
Regularities in natural language systems, despite their cognitive advantages in terms of storage ... more Regularities in natural language systems, despite their cognitive advantages in terms of storage and learnability, often coexist with exceptions, raising the question of whether and why irregularities survive. We offer a complex system perspective on this issue, focusing on the irregular past tense forms in English. Two separate processes affect the overall regularity: new verbs constantly entering the vocabulary in the regular form at low frequency, and transitions in both directions (from irregular to regular and vice-versa) occurring in a narrow frequency range. The introduction of new verbs leads to an increase in regular types, that, entering at low frequencies, have a small impact on the perceived irregularity in terms of tokens. The frequency of usage acts as a control parameter, the majority of verbs types being fully-regular(irregular) at low(high) frequencies, with no evidence of irregularity facing extinction. Very few verbs types in an intermediate frequency region exhib...
Physical Review E, 2019
The spread of an infectious disease can be promoted by previous infections with other pathogens. ... more The spread of an infectious disease can be promoted by previous infections with other pathogens. This cooperative effect can give rise to violent outbreaks, reflecting the presence of an abrupt epidemic transition. As for other diffusive dynamics, the topology of the interaction pattern of the host population plays a crucial role. It was conjectured that a discontinuous transition arises when there are relatively few short loops and many long loops in the contact network. Here we focus on the role of local clustering in determining the nature of the transition. We consider two mutually cooperative pathogens diffusing in the same population: An individual already infected with one disease has an increased probability of getting infected by the other. We look at how a disease obeying the susceptible-infected-removed dynamics spreads on contact networks with tunable clustering. Using numerical simulations we show that for large cooperativity the epidemic transition is always abrupt, with the discontinuity decreasing as clustering is increased. For large clustering strong finite-size effects are present and the discontinuous nature of the transition is manifest only in large networks. We also investigate the problem of influential spreaders for cooperative infections, revealing that both cooperativity and clustering strongly enhance the dependence of the spreading influence on the degree of the initial seed.
Physical Review E, 2017
The spread of an infectious disease can, in some cases, promote the propagation of other pathogen... more The spread of an infectious disease can, in some cases, promote the propagation of other pathogens favoring violent outbreaks, which cause a discontinuous transition to an endemic state. The topology of the contact network plays a crucial role in these cooperative dynamics. We consider a susceptible-infected-removed-type model with two mutually cooperative pathogens: An individual already infected with one disease has an increased probability of getting infected by the other. We present a heterogeneous mean-field theoretical approach to the coinfection dynamics on generic uncorrelated power-law degree-distributed networks and validate its results by means of numerical simulations. We show that, when the second moment of the degree distribution is finite, the epidemic transition is continuous for low cooperativity, while it is discontinuous when cooperativity is sufficiently high. For scale-free networks, i.e., topologies with diverging second moment, the transition is instead always continuous. In this way we clarify the effect of heterogeneity and system size on the nature of the transition, and we validate the physical interpretation about the origin of the discontinuity.
Physical Review E, 2015
Messages conveyed by media act as a major drive in shaping attitudes and inducing opinion shift. ... more Messages conveyed by media act as a major drive in shaping attitudes and inducing opinion shift. On the other hand, individuals are strongly affected by peer pressure while forming their own judgment. We solve a general model of opinion dynamics where individuals either hold one of two alternative opinions or are undecided and interact pairwise while exposed to an external influence. As media pressure increases, the system moves from pluralism to global consensus; four distinct classes of collective behavior emerge, crucially depending on the outcome of direct interactions among individuals holding opposite opinions. Observed nontrivial behaviors include hysteretic phenomena and resilience of minority opinions. Notably, consensus could be unachievable even when media and microscopic interactions are biased in favor of the same opinion: The unfavored opinion might even gain the support of the majority.
We consider a general class of three–state models where individuals hold one of two opposite opin... more We consider a general class of three–state models where individuals hold one of two opposite opinions, or are neutral, and exchange opinions in generic pairwise interactions. We show that when opinions spread in a population where a fraction of individuals (zealots) maintain unshakably their opinion, one of four qualitatively distinct kinds of collective dynamics arise, depending on the specific rules governing the social interactions. Unsurprisingly, when their density is high, zealots drive the whole population to consensus on their opinion. For low densities a rich phase diagram emerges: a finite population of dissenters can survive and be the only stationary state or may need a critical mass or dissenters to be sustained; the critical mass may vanish or not as the density is reduced; the transition to the high density regime can be smooth or abrupt, and shows interesting hysteretic effects. For each choice of the interaction rules we calculate the critical density of zealots above which diverse opinions cannot survive.
EPL (Europhysics Letters), 2013
The evolutionary dynamics of human Influenza A virus presents a challenging theoretical problem. ... more The evolutionary dynamics of human Influenza A virus presents a challenging theoretical problem. An extremely high mutation rate allows the virus to escape, at each epidemic season, the host immune protection elicited by previous infections. At the same time, at each given epidemic season a single quasi-species, that is a set of closely related strains, is observed. A non-trivial relation between the genetic (i.e., at the sequence level) and the antigenic (i.e., related to the host immune response) distances can shed light into this puzzle. In this paper we introduce a model in which, in accordance with experimental observations, a simple interaction rule based on spatial correlations among point mutations dynamically defines an immunity space in the space of sequences. We investigate the static and dynamic structure of this space and we discuss how it affects the dynamics of the virus-host interaction. Interestingly we observe a staggered time structure in the virus evolution as in the real Influenza evolutionary dynamics.
ABSTRACT We analyze the spectral properties of complex networks focusing on their relation to the... more ABSTRACT We analyze the spectral properties of complex networks focusing on their relation to the community structure, and develop an algorithm based on correlations among components of different eigenvectors. The algorithm applies to general weighted networks, and, in a suitably modified version, to the case of directed networks. Our method allows to correctly detect communities in sharply partitioned graphs, however it is useful to the analysis of more complex networks, without a well defined cluster structure, as social and information networks. As an example, we test the algorithm on a large scale data-set from a psychological experiment of free word association, where it proves to be successful both in clustering words, and in uncovering mental association patterns.
Lecture Notes in Computer Science, 2004
We develop an algorithm to detect community structure in complex networks. The algorithm is based... more We develop an algorithm to detect community structure in complex networks. The algorithm is based on spectral methods and takes into account weights and links orientations. Since the method detects efficiently clustered nodes in large networks even when these are not sharply partitioned, it turns to be specially suitable to the analysis of social and information networks. We test the algorithm on a large-scale data-set from a psychological experiment of word association. In this case, it proves to be successful both in clustering words, and in uncovering mental association patterns.
We develop an algorithm to detect community structure in complex networks. The algorithm is based... more We develop an algorithm to detect community structure in complex networks. The algorithm is based on spectral methods and takes into account weights and link orientation. Since the method detects efficiently clustered nodes in large networks even when these are not sharply partitioned, it turns to be specially suitable for the analysis of social and information networks. We test the algorithm on a large-scale data-set from a psychological experiment of word association. In this case, it proves to be successful both in clustering words, and in uncovering mental association patterns. r Measurements and exact results concerning the clustering patterns of networks mainly concern the occurrence of regular motifs [1-4] and their correlations . However, many social and information networks, such as the World Wide Web, turn out to be approximately partitioned into communities of irregular shape: for example web pages focusing on similar topics are strongly mutually connected and have a weaker linkage to the rest of the Web. The design of methods to partition a ARTICLE IN PRESS www.elsevier.com/locate/physa 0378-4371/$ -see front matter r
Empirical evidence shows that the rate of irregular usage of English verbs exhibits discontinuity... more Empirical evidence shows that the rate of irregular usage of English verbs exhibits discontinuity as a function of their frequency: the most frequent verbs tend to be totally irregular. We aim to qualitatively understand the origin of this feature by studying simple agent-based models of language dynamics, where each agent adopts an inflectional state for a verb and may change it upon interaction with other agents. At the same time, agents are replaced at some rate by new agents adopting the regular form. In models with only two inflectional states (regular and irregular), we observe that either all verbs regularize irrespective of their frequency, or a continuous transition occurs between a low-frequency state, where the lemma becomes fully regular, and a high-frequency one, where both forms coexist. Introducing a third (mixed) state, wherein agents may use either form, we find that a third, qualitatively different behavior may emerge, namely, a discontinuous transition in frequency. We introduce and solve analytically a very general class of three-state models that allows us to fully understand these behaviors in a unified framework. Realistic sets of interaction rules, including the well-known naming game (NG) model, result in a discontinuous transition, in agreement with recent empirical findings. We also point out that the distinction between speaker and hearer in the interaction has no effect on the collective behavior. The results for the general three-state model, although discussed in terms of language dynamics, are widely applicable.
Rules are an efficient feature of natural languages which allow speakers to use a finite set of i... more Rules are an efficient feature of natural languages which allow speakers to use a finite set of instructions to generate a virtually infinite set of utterances. Yet, for many regular rules, there are irregular exceptions. There has been lively debate in cognitive science about how individual learners acquire rules and exceptions; for example, how they learn the past tense of preach is preached, but for teach it is taught. However, for most population or language-level models of language structure, particularly from the perspective of language evolution, the goal has generally been to examine how languages evolve stable structure, and neglects the fact that in many cases, languages exhibit exceptions to structural rules. We examine the dynamics of regularity and irregularity across a population of interacting agents to investigate how, for example, the irregular teach coexists beside the regular preach in a dynamic language system. Models show that in the absence of individual biases towards either regularity or irregularity, the outcome of a system is determined entirely by the initial condition. On the other hand, in the presence of individual biases, rule systems exhibit frequency dependent patterns in regularity reminiscent of patterns in natural language. We implement individual biases towards regularity in two ways: through 'child' agents who have a preference to generalise using the regular form, and through a memory constraint wherein an agent can only remember an irregular form for a finite time period. We provide theoretical arguments for the prediction of a critical frequency below which irregularity cannot persist in terms of the duration of the finite time period which constrains agent memory. Further, within our framework we also find stable irregularity, arguably a feature of most natural languages not accounted for in many other cultural models of language structure.
We show that the problem of directed percolation on an arbitrary lattice is equivalent to the pro... more We show that the problem of directed percolation on an arbitrary lattice is equivalent to the problem of m directed random walkers with rather general attractive interactions, when suitably continued to m 0. In 1 1 1 dimensions, this is dual to a model of interacting steps on a vicinal surface. A similar correspondence with interacting self-avoiding walks is constructed for isotropic percolation. [S0031-9007(99)08735-9] PACS numbers: 05.40. -a, 05.50. + q, 64.60.Ak
Physica A: Statistical Mechanics and its Applications, 2015
We investigate degree correlations in two online social networks where users are connected throug... more We investigate degree correlations in two online social networks where users are connected through different types of links. We find that, while subnetworks in which links have a positive connotation, such as endorsement and trust, are characterized by assortative mixing by degree, networks in which links have a negative connotation, such as disapproval and distrust, are characterized by disassortative patterns. We introduce a class of simple theoretical models to analyze the interplay between network topology and the superimposed structure based on the sign of links. Results uncover the conditions that underpin the emergence of the patterns observed in the data, namely the assortativity of positive subnetworks and the disassortativity of negative ones. We discuss the implications of our study for the analysis of signed complex networks.
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Papers by Francesca Colaiori