@article{mihelcic2017framework,
author = "Matej Mihel{\v{c}}i{\'{c}} and Sa{\v{s}}o D{\v{z}}eroski and Nada Lavra{\v{c}} and Tomislav {\v{S}}muc",
abstract = "Redescription mining is a field of knowledge discovery that aims at finding different descriptions of similar subsets of instances in the data. These descriptions are represented as rules inferred from one or more disjoint sets of attributes, called views. As such, they support knowledge discovery process and help domain experts in formulating new hypotheses or constructing new knowledge bases and decision support systems. In contrast to previous approaches that typically create one smaller set of redescriptions satisfying a pre-defined set of constraints, we introduce a framework that creates large and heterogeneous redescription set from which user/expert can extract compact sets of differing properties, according to its own preferences. Construction of large and heterogeneous redescription set relies on CLUS-RM algorithm and a novel, conjunctive refinement procedure that facilitates generation of larger and more accurate redescription sets. The work also introduces the variability of redescription accuracy when missing values are present in the data, which significantly extends applicability of the method. Crucial part of the framework is the redescription set extraction based on heuristic multi-objective optimization procedure that allows user to define importance levels towards one or more redescription quality criteria. We provide both theoretical and empirical comparison of the novel framework against current state of the art redescription mining algorithms and show that it represents more efficient and versatile approach for mining redescriptions from data.",
doi = "10.1016/j.eswa.2016.10.012",
issn = "09574174",
journal = "Expert Systems with Applications",
pages = "196--215",
title = "{A} framework for redescription set construction",
volume = "68",
year = "2017",
}
@article{bardoscia2016distress,
author = "Marco Bardoscia and Fabio Caccioli and Juan Ignacio Perotti and Gianna Vivaldo and Guido Caldarelli",
abstract = "We consider a dynamical model of distress propagation on complex networks, which we apply to the study of financial contagion in networks of banks connected to each other by direct exposures. The model that we consider is an extension of the DebtRank algorithm, recently introduced in the literature. The mechanics of distress propagation is very simple: When a bank suffers a loss, distress propagates to its creditors, who in turn suffer losses, and so on. The original DebtRank assumes that losses are propagated linearly between connected banks. Here we relax this assumption and introduce a one-parameter family of non-linear propagation functions. As a case study, we apply this algorithm to a data-set of 183 European banks, and we study how the stability of the system depends on the non-linearity parameter under different stress-test scenarios. We find that the system is characterized by a transition between a regime where small shocks can be amplified and a regime where shocks do not propagate, and that the overall the stability of the system increases between 2008 and 2013.",
journal = "PLoS ONE",
month = "dec",
pages = "e0163825",
title = "{D}istress propagation in complex networks: the case of non-linear {D}ebt{R}ank",
url = "http://arxiv.org/abs/1512.04460",
volume = "11",
year = "2016",
}
@incollection{wider2016interconnected,
author = "Nicolas Wider and Antonios Garas and Ingo Scholtes and Frank Schweitzer",
abstract = "In this work we analyze the architecture of real urban mobility networks from the multiplex perspective. In particular, based on empirical data about the mobility patterns in the cities of Bogot$\backslash$'a and Medell$\backslash$'{\{}$\backslash$i{\}}n, each city is represented by six multiplex networks, each one representing the origin-destination trips performed by a subset of the population corresponding to a particular socioeconomic status. The nodes of each multiplex are the different urban locations whereas links represent the existence of a trip from one node (origin) to another (destination). On the other hand, the different layers of each multiplex correspond to the different existing transportation modes. By exploiting the characterization of multiplex transportation networks combining different transportation modes, we aim at characterizing the mobility patterns of each subset of the population. Our results show that the socioeconomic characteristics of the population have an extraordinary impact in the layer organization of these multiplex systems.",
booktitle = "Interconnected Networks",
doi = "10.1007/978-3-319-23947-7",
isbn = "978-3-319-23945-3",
issn = "15440591",
pages = "149--164",
title = "{I}nterconnected {N}etworks",
url = "http://arxiv.org/abs/1408.2484$\backslash$nhttp://link.springer.com/10.1007/978-3-319-23947-7",
year = "2016",
}
@article{vestergaard2016impact,
author = "Christian L Vestergaard and Eugenio Valdano and Mathieu G{\'e}nois and Chiara Poletto and Vittoria Colizza and Alain Barrat",
abstract = "The ability to directly record human face-to-face interactions increasingly enables the development of detailed data-driven models for the spread of directly transmitted infectious diseases at the scale of individuals. Complete coverage of the contacts occurring in a population is however generally unattainable, due for instance to limited participation rates or experimental constraints in spatial coverage. Here, we study the impact of spatially constrained sampling on our ability to estimate the epidemic risk in a population using such detailed data-driven models. The epidemic risk is quantified by the epidemic threshold of the SIRS model for the propagation of communicable diseases, i.e. the critical value of disease transmissibility above which the disease turns endemic. We verify for both synthetic and empirical data of human interactions that the use of incomplete data sets due to spatial sampling leads to the underestimation of the epidemic risk. The bias is however smaller than the one obtained by uniformly sampling the same fraction of contacts: it depends non-linearly on the fraction of contacts that are recorded, and becomes negligible if this fraction is large enough. Moreover, it depends on the interplay between the timescales of population and spreading dynamics.",
doi = "10.1017/S0956792516000309",
isbn = "0956792516000",
issn = "0956-7925",
journal = "European Journal of Applied Mathematics",
keywords = "disease spreading;network epidemiology;network sampling",
pages = "1--17",
title = "{I}mpact of spatially constrained sampling of temporal contact networks on the evaluation of the epidemic risk",
url = "http://www.journals.cambridge.org/abstract{\_}S0956792516000309",
year = "2016",
}
@article{vivaldo2016networks,
author = "Gianna Vivaldo and Elisa Masi and Camilla Pandolfi and Stefano Mancuso and Guido Caldarelli",
abstract = "Despite the common misconception of nearly static organisms, plants do interact continuously with the environment and with each other. It is fair to assume that during their evolution they developed particular features to overcome problems and to exploit possibilities from environment. In this paper we introduce various quantitative measures based on recent advancements in complex network theory that allow to measure the effective similarities of various species. By using this approach on the similarity in fruit-typology ecological traits we obtain a clear plant classification in a way similar to traditional taxonomic classification. This result is not trivial, since a similar analysis done on the basis of diaspore morphological properties do not provide any clear parameter to classify plants species. Complex network theory can then be used in order to determine which feature amongst many can be used to distinguish scope and possibly evolution of plants. Future uses of this approach range from functional classification to quantitative determination of plant communities in nature.",
doi = "10.1038/srep27077",
issn = "2045-2322",
journal = "Nature Publishing Group",
number = "February",
pages = "1--11",
publisher = "Nature Publishing Group",
title = "{N}etworks of plants: how to measure similarity in vegetable species",
url = "http://arxiv.org/abs/1602.05887",
year = "2016",
}
@article{vodenska2016community,
author = "Irena Vodenska and Alexander P Becker and Di Zhou and Dror Y Kenett and H Eugene Stanley and Shlomo Havlin",
doi = "10.3390/risks4020013",
issn = "2227-9091",
journal = "Risks",
keywords = "community structure;complex networks;financial markets",
pages = "13--28",
title = "{C}ommunity {A}nalysis of {G}lobal {F}inancial {M}arkets",
volume = "4",
year = "2016",
}
@article{sole-ribalta2016random,
author = "Albert Sol{\'e}-Ribalta and Manlio {De Domenico} and Sergio G{\'o}mez and Alex Arenas",
abstract = "Real-world complex systems exhibit multiple levels of relationships. In many cases they require to be modeled as interconnected multilayer networks, characterizing interactions of several types simultaneously. It is of crucial importance in many fields, from economics to biology and from urban planning to social sciences, to identify the most (or the less) influent nodes in a network using centrality measures. However, defining the centrality of actors in interconnected complex networks is not trivial. In this paper, we rely on the tensorial formalism recently proposed to characterize and investigate this kind of complex topologies, and extend two well known random walk centrality measures, the random walk betweenness and closeness centrality, to interconnected multilayer networks. For each of the measures we provide analytical expressions that completely agree with numerically results.",
doi = "10.1016/j.physd.2016.01.002",
isbn = "2041-1723 (Electronic)$\backslas",
issn = "01672789",
journal = "Physica D: Nonlinear Phenomena",
keywords = "Centrality;Multilayer complex networks;Random walks",
pages = "73--79",
publisher = "Elsevier B.V.",
title = "{R}andom walk centrality in interconnected multilayer networks",
url = "http://dx.doi.org/10.1016/j.physd.2016.01.002",
volume = "323-324",
year = "2016",
}
@article{skardal2016collective,
author = "Per Sebastian Skardal and Dane Taylor and Jie Sun and Alex Arenas",
abstract = "A wide range of natural and engineered phenomena rely on large networks of interacting units to reach a dynamical consensus state where the system collectively operates. Here we study the dynamics of self-organizing systems and show that for generic directed networks the collective frequency of the ensemble is not the same as the mean of the individuals' natural frequencies. Specifically, we show that the collective frequency equals a weighted average of the natural frequencies, where the weights are given by an out-flow centrality measure that is equivalent to a reverse PageRank centrality. Our findings uncover an intricate dependence of the collective frequency on both the structural directedness and dynamical heterogeneity of the network, and also reveal an unexplored connection between synchronization and PageRank, which opens the possibility of applying PageRank optimization to synchronization. Finally, we demonstrate the presence of collective frequency variation in real-world networks by considering the UK and Scandinavian power grids.",
doi = "10.1103/PhysRevE.93.042314",
issn = "15502376",
journal = "Physical Review E - Statistical, Nonlinear, and Soft Matter Physics",
number = "4",
pages = "1--7",
title = "{C}ollective frequency variation in network synchronization and reverse {P}age{R}ank",
volume = "93",
year = "2016",
}
@article{skardal2016erosion,
author = "Per Sebastian Skardal and Dane Taylor and Jie Sun and Alex Arenas",
abstract = "We study the dynamics of network-coupled phase oscillators in the presence of coupling frustration. It was recently demonstrated that in heterogeneous network topologies, the presence of coupling frustration causes perfect phase synchronization to become unattainable even in the limit of infinite coupling strength. Here, we consider the important case of heterogeneous coupling functions and extend previous results by deriving analytical predictions for the total erosion of synchronization. Our analytical results are given in terms of basic quantities related to the network structure and coupling frustration. In addition to fully heterogeneous coupling, where each individual interaction is allowed to be distinct, we also consider partially heterogeneous coupling and homogeneous coupling in which the coupling functions are either unique to each oscillator or identical for all network interactions, respectively. We demonstrate the validity of our theory with numerical simulations of multiple network models, and highlight the interesting effects that various coupling choices and network models have on the total erosion of synchronization. Finally, we consider some special network structures with well-known spectral properties, which allows us to derive further analytical results.",
doi = "10.1016/j.physd.2015.10.015",
issn = "01672789",
journal = "Physica D: Nonlinear Phenomena",
keywords = "Complex networks;Nonlinear dynamics;Synchronization",
pages = "40--48",
publisher = "Elsevier B.V.",
title = "{E}rosion of synchronization: {C}oupling heterogeneity and network structure",
url = "http://dx.doi.org/10.1016/j.physd.2015.10.015",
volume = "323-324",
year = "2016",
}
@conference{sluban2016temporal,
author = "Borut Sluban and Miha Gr{\v{c}}ar and Igor Mozeti{\v{c}}",
abstract = "Good news should answer the following questions: 'Who?', 'Where?', 'When?', 'What?', and possibly 'Why?'. We present an ap-proach which extracts interesting events from thousands of daily news. We construct a time-varying, three-layer network where the nodes are entities of interest in the news. The temporal aspect of the network an-swers the 'When?' question. The layers are: 1) the co-occurrence of enti-ties which answers the 'Who?' or 'Where?', 2) the summary layer which answers the 'What?', and 3) the sentiment layer which labels the links as 'good' or 'bad' news. We demonstrate the news network evolution over a period of four years in an interactive web portal.",
booktitle = "Proc. 7th Workshop on Complex Networks CompleNet",
keywords = "multi-layer networks;sentiment;sum-marization;temporal networks",
pages = "29--41",
publisher = "Springer",
title = "{T}emporal {M}ulti-layer {N}etwork {C}onstruction from {M}ajor {N}ews {E}vents",
url = "http://dx.doi.org/10.1007/978-3-319-30569-1{\_}3",
year = "2016",
}
@article{smieszek2016contact,
author = "Timo Smieszek and Stefanie Castell and Alain Barrat and Ciro Cattuto and Peter J White and G{\'e}rard Krause",
abstract = "BACKGROUND Studies measuring contact networks have helped to improve our understanding of infectious disease transmission. However, several methodological issues are still unresolved, such as which method of contact measurement is the most valid. Further, complete network analysis requires data from most, ideally all, members of a network and, to achieve this, acceptance of the measurement method. We aimed at investigating measurement error by comparing two methods of contact measurement - paper diaries vs. wearable proximity sensors - that were applied concurrently to the same population, and we measured acceptability. METHODS We investigated the contact network of one day of an epidemiology conference in September 2014. Seventy-six participants wore proximity sensors throughout the day while concurrently recording their contacts with other study participants in a paper-diary; they also reported on method acceptability. RESULTS There were 329 contact reports in the paper diaries, corresponding to 199 contacts, of which 130 were noted by both parties. The sensors recorded 316 contacts, which would have resulted in 632 contact reports if there had been perfect concordance in recording. We estimated the probabilities that a contact was reported in a diary as: P = 72 {\%} for {\textless}5 min contact duration (significantly lower than the following, p {\textless} 0.05), P = 86 {\%} for 5-15 min, P = 89 {\%} for 15-60 min, and P = 94 {\%} for {\textgreater}60 min. The sets of sensor-measured and self-reported contacts had a large intersection, but neither was a subset of the other. Participants' aggregated contact duration was mostly substantially longer in the diary data than in the sensor data. Twenty percent of respondents ({\textgreater}1 reported contact) stated that filling in the diary was too much work, 25 {\%} of respondents reported difficulties in remembering contacts, and 93 {\%} were comfortable having their conference contacts measured by sensors. CONCLUSION Reporting and recording were not complete; reporting was particularly incomplete for contacts {\textless}5 min. The types of contact that both methods are capable of detecting are partly different. Participants appear to have overestimated the duration of their contacts. Conducting a study with diaries or wearable sensors was acceptable to and mostly easily done by participants. Both methods can be applied meaningfully if their specific limitations are considered and incompleteness is accounted for.",
doi = "10.1186/s12879-016-1676-y",
issn = "1471-2334",
journal = "BMC infectious diseases",
keywords = "Acceptability;Contact diary;Contact network;Infection transmission;Infectious disease;Measurement error;Network epidemiology;Network model;Proximity sensor;RFID",
pages = "341",
publisher = "BMC Infectious Diseases",
title = "{C}ontact diaries versus wearable proximity sensors in measuring contact patterns at a conference: method comparison and participants' attitudes.",
url = "http://www.ncbi.nlm.nih.gov/pubmed/27449511$\backslash$nhttp://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4957345",
volume = "16",
year = "2016",
}
@article{shekhtman2015recent,
author = "Louis M. Shekhtman and Michael M. Danziger and Shlomo Havlin",
abstract = "Until recently, network science has focused on the properties of single isolated networks that do not interact or depend on other networks. However it has now been recognized that many real-networks, such as power grids, transportation systems, and communication infrastructures interact and depend on other networks. Here, we will present a review of the framework developed in recent years for studying the vulnerability and recovery of networks composed of interdependent networks. In interdependent networks, when nodes in one network fail, they cause dependent nodes in other networks to also fail. This is also the case when some nodes, like for example certain people, play a role in two networks, i.e. in a multiplex. Dependency relations may act recursively and can lead to cascades of failures concluding in sudden fragmentation of the system. We review the analytical solutions for the critical threshold and the giant component of a network of n interdependent networks. The general theory and behavior of interdependent networks has many novel features that are not present in classical network theory. Interdependent networks embedded in space are significantly more vulnerable compared to non-embedded networks. In particular, small localized attacks may lead to cascading failures and catastrophic consequences. Finally, when recovery of components is possible, global spontaneous recovery of the networks and hysteresis phenomena occur. The theory developed for this process points to an optimal repairing strategy for a network of networks. Understanding realistic effects present in networks of networks is required in order to move towards determining system vulnerability.",
doi = "10.1016/j.chaos.2016.02.002",
isbn = "0960-0779",
issn = "09600779",
journal = "Chaos, Solitons and Fractals",
keywords = "Complex matter and networks;Interdependent networks;Percolation Theory",
pages = "28--36",
publisher = "Elsevier Ltd",
title = "{R}ecent advances on failure and recovery in networks of networks",
url = "http://dx.doi.org/10.1016/j.chaos.2016.02.002",
volume = "90",
year = "2016",
}
@article{skardal2016controlling,
author = "Per Sebastian Skardal and Alex Arenas",
abstract = "The control of network-coupled nonlinear dynamical systems is an active area of research in the nonlinear science community. Coupled oscillator networks represent a particularly important family of nonlinear systems, with applications ranging from the power grid to cardiac excitation. Here we study the control of network-coupled limit cycle oscillators, extending previous work that focused on phase oscillators. Based on stabilizing a target fixed point, our method aims to attain complete frequency synchronization, i.e., consensus, by applying control to as few oscillators as possible. We develop two types of control. The first type directs oscillators towards to larger amplitudes, while the second does not. We present numerical examples of both control types and comment on the potential failures of the method.",
doi = "10.1063/1.4954273",
issn = "10541500",
journal = "Chaos",
number = "9",
title = "{O}n controlling networks of limit-cycle oscillators",
volume = "26",
year = "2016",
}
@article{scholtes2016higher,
author = "Ingo Scholtes and Nicolas Wider and Antonios Garas",
abstract = "Recent research on temporal networks has highlighted the limitations of a static network perspective for our understanding of complex systems with dynamic topologies. In particular, recent works have shown that i) the specific order in which links occur in real-world temporal networks affects causality structures and thus the evolution of dynamical processes, and ii) higher-order aggregate representations of temporal networks can be used to analytically study the effect of these order correlations on dynamical processes. In this article we analyze the effect of order correlations on path-based centrality measures in real-world temporal networks. Analyzing temporal equivalents of betweenness, closeness and reach centrality in six empirical temporal networks, we first show that an analysis of the commonly used static, time-aggregated representation can give misleading results about the actual importance of nodes. We further study higher-order time-aggregated networks, a recently proposed generalization of the commonly applied static, time-aggregated representation of temporal networks. Here, we particularly define path-based centrality measures based on second-order aggregate networks, empirically validating that node centralities calculated in this way better capture the true temporal centralities of nodes than node centralities calculated based on the commonly used static (first-order) representation. Apart from providing a simple and practical method for the approximation of path-based centralities in temporal networks, our results highlight interesting perspectives for the use of higher-order aggregate networks in the analysis of time-stamped network data.",
doi = "10.1140/epjb/e2016-60663-0",
isbn = "2016606630",
issn = "14346036",
journal = "European Physical Journal B",
number = "3",
pages = "1--15",
title = "{H}igher-order aggregate networks in the analysis of temporal networks: path structures and centralities",
volume = "89",
year = "2016",
}
@article{sendina-nadal2016assortativity,
author = "I. Sendi{\~n}a-Nadal and M. M. Danziger and Z. Wang and S. Havlin and S. Boccaletti",
abstract = "Many real-world networks exhibit degree-assortativity, with nodes of similar degree more likely to link to one another. Particularly in social networks, the contribution to the total assortativity varies with degree, featuring a distinctive peak slightly past the average degree. The way traditional models imprint assortativity on top of pre-defined topologies is via degree-preserving link permutations, which however destroy the particular graph's hierarchical traits of clustering. Here, we propose the first generative model which creates heterogeneous networks with scale-free-like properties and tunable realistic assortativity. In our approach, two distinct populations of nodes are added to an initial network seed: one (the followers) that abides by usual preferential rules, and one (the potential leaders) connecting via anti-preferential attachments, i.e. selecting lower degree nodes for their initial links. The latter nodes come to develop a higher average degree, and convert eventually into the final hubs. Examining the evolution of links in Facebook, we present empirical validation for the connection between the initial anti-preferential attachment and long term high degree. Thus, our work sheds new light on the structure and evolution of social networks.",
doi = "10.1038/srep21297",
issn = "2045-2322",
journal = "Scientific Reports",
number = "October 20",
pages = "21297",
publisher = "Nature Publishing Group",
title = "{A}ssortativity and leadership emerge from anti-preferential attachment in heterogeneous networks",
url = "http://arxiv.org/abs/1508.03528$\backslash$nhttp://www.nature.com/articles/srep21297",
volume = "6",
year = "2016",
}
@article{sapienza2016detecting,
author = "Anna Sapienza and Andre Panisson and Joseph Wu and Laetitia Gauvin and Ciro Cattuto",
doi = "10.1109/ICDMW.2015.128",
isbn = "9781467384926",
journal = "Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015",
pages = "516--523",
title = "{D}etecting {A}nomalies in {T}ime-{V}arying {N}etworks {U}sing {T}ensor {D}ecomposition",
year = "2016",
}
@article{ranco2016coupling,
author = "Gabriele Ranco and Ilaria Bordino and Giacomo Bormetti and Guido Caldarelli and Fabrizio Lillo and Michele Treccani",
abstract = "The new digital revolution of big data is deeply changing our capability of understanding society and forecasting the outcome of many social and economic systems. Unfortunately, information can be very heterogeneous in the importance, relevance, and surprise it conveys, affecting severely the predictive power of semantic and statistical methods. Here we show that the aggregation of web users' behavior can be elicited to overcome this problem in a hard to predict complex system, namely the financial market. Specifically, our in-sample analysis shows that the combined use of sentiment analysis of news and browsing activity of users of Yahoo! Finance greatly helps forecasting intra-day and daily price changes of a set of 100 highly capitalized US stocks traded in the period 2012-2013. Sentiment analysis or browsing activity when taken alone have very small or no predictive power. Conversely, when considering a news signal where in a given time interval we compute the average sentiment of the clicked news, weighted by the number of clicks, we show that for nearly 50{\%} of the companies such signal Granger-causes hourly price returns. Our result indicates a "wisdom-of-the-crowd" effect that allows to exploit users' activity to identify and weigh properly the relevant and surprising news, enhancing considerably the forecasting power of the news sentiment.",
doi = "10.1371/journal.pone.0146576",
issn = "1932-6203",
journal = "PloS one",
number = "1",
pages = "e0146576",
title = "{C}oupling {N}ews {S}entiment with {W}eb {B}rowsing {D}ata {I}mproves {P}rediction of {I}ntra-{D}ay {P}rice {D}ynamics.",
url = "http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0146576",
volume = "11",
year = "2016",
}
@incollection{rozenblat2016multipolar,
author = "C{\'e}line Rozenblat and F. Zaidi and A. Bellwald",
booktitle = "Global Networks",
title = "{T}he multipolar regionalization of world cities in the multinational firms networks",
year = "2016",
}
@article{poncela-casasnovas2016humans,
author = "Julia Poncela-Casasnovas and Mario Guti{\'e}rrez-Roig and Carlos Gracia-L{\'a}zaro and Julian Vicens and Jes{\'u}s G{\'o}mez-Garde{\~n}es and Josep Perell{\'o} and Yamir Moreno and Jordi Duch and Angel S{\'a}nchez",
abstract = "Socially relevant situations that involve strategic interactions are widespread among animals and humans alike. To study these situations, theoretical and experimental research has adopted a game theoretical perspective, generating valuable insights about human behavior. However, most of the results reported so far have been obtained from a population perspective and considered one specific conflicting situation at a time. This makes it difficult to extract conclusions about the consistency of individuals' behavior when facing different situations and to define a comprehensive classification of the strategies underlying the observed behaviors. We present the results of a lab-in-the-field experiment in which subjects face four different dyadic games, with the aim of establishing general behavioral rules dictating individuals' actions. By analyzing our data with an unsupervised clustering algorithm, we find that all the subjects conform, with a large degree of consistency, to a limited number of behavioral phenotypes (envious, optimist, pessimist, and trustful), with only a small fraction of undefined subjects. We also discuss the possible connections to existing interpretations based on a priori theoretical approaches. Our findings provide a relevant contribution to the experimental and theoretical efforts toward the identification of basic behavioral phenotypes in a wider set of contexts without aprioristic assumptions regarding the rules or strategies behind actions. From this perspective, our work contributes to a fact-based approach to the study of human behavior in strategic situations, which could be applied to simulating societies, policy-making scenario building, and even a variety of business applications.",
doi = "10.1126/sciadv.1600451",
issn = "2375-2548",
journal = "Science advances",
number = "8",
pages = "e1600451",
title = "{H}umans display a reduced set of consistent behavioral phenotypes in dyadic games.",
url = "http://arxiv.org/abs/1608.02015",
volume = "2",
year = "2016",
}
@conference{pacuk2016twitter,
author = "Andrzej Pacuk and Piotr Sankowski and W Karol and Piotr Wygocki",
abstract = "How information spreads through a social network? Can we assume, that the information is spread only through a given social network graph? What is the correct way to compare the models of information flow? These are the basic questions we address in this work. We focus on meticulous comparison of various, well-known models of rumor propagation in the social network. We introduce the model incorporating mass media and effects of absent nodes. In this model the information appears spontaneously in the graph. Using the most conservative metric, we showed that the distribution of cascades sizes generated by this model fits the real data much better than the previously considered models.",
booktitle = "HT'16",
doi = "10.1145/2914586.2914623",
isbn = "9781450342476",
keywords = "cascades size distribution;social network analysis;social networks;twitter",
pages = "279--284",
title = "{T}here is {S}omething {B}eyond the {T}witter {N}etwork",
year = "2016",
}
@article{pacuk2016locality,
author = "Andrzej Pacuk and Piotr Sankowski and Karol Wegrzycki and Piotr Wygocki",
abstract = "We consider the problem of reconciling gene trees with a species tree based on the widely accepted Gene Duplication model$\backslash$n from Goodman et al. Current algorithms that solve this problem handle only binary gene trees or interpret polytomies in the gene tree as true.$\backslash$n While in practice polytomies occur frequently, they are typically not true. Most polytomies represent unresolved evolutionary$\backslash$n relationships. In this case a polytomy is called apparent. In this work we modify the problem of reconciling gene and species trees by interpreting polytomies to be apparent, based$\backslash$n on a natural extension of the Gene Duplication model. We further provide polynomial time algorithms to solve this modified$\backslash$n problem.",
doi = "10.1007/s00453-016-0176-1",
isbn = "978-3-540-36925-7",
issn = "14320541",
journal = "LNCS",
pages = "105--118",
title = "{L}ocality-sensitive hashing without false negatives for lp",
volume = "9797",
year = "2016",
}
@article{palchykov2016ground,
author = "Vasyl Palchykov and Valerio Gemmetto and Alexey Boyarsky and Diego Garlaschelli",
abstract = "Community detection techniques are widely used to infer hidden structures within interconnected systems. Despite demonstrating high accuracy on benchmarks, they reproduce the external classification for many real-world systems with a significant level of discrepancy. A widely accepted reason behind such outcome is the unavoidable loss of non-topological information (such as node attributes) encountered when the original complex system is represented as a network. In this article we emphasize that the observed discrepancies may also be caused by a different reason: the external classification itself. For this end we use scientific publication data which i) exhibit a well defined modular structure and ii) hold an expert-made classification of research articles. Having represented the articles and the extracted scientific concepts both as a bipartite network and as its unipartite projection, we applied modularity optimization to uncover the inner thematic structure. The resulting clusters are shown to partly reflect the author-made classification, although some significant discrepancies are observed. A detailed analysis of these discrepancies shows that they carry essential information about the system, mainly related to the use of similar techniques and methods across different (sub)disciplines, that is otherwise omitted when only the external classification is considered.",
doi = "10.1140/epjds/s13688-016-0090-4",
isbn = "1368801600904",
issn = "21931127",
journal = "EPJ Data Science",
keywords = "bipartite networks;community detection;science of science",
number = "1",
publisher = "Palchykov et al.",
title = "{G}round truth? {C}oncept-based communities versus the external classification of physics manuscripts",
url = "http://dx.doi.org/10.1140/epjds/s13688-016-0090-4",
volume = "5",
year = "2016",
}
@techreport{piskorec2016modeling,
author = "Matija Pi{\v{s}}korec and Nino Antulov-Fantulin and Iva Miholi{\'{c}} and Tomislav {\v{S}}muc and Mile {\v{S}}iki{\'{c}}",
abstract = "Opinion polls mediated through a social network can give us, in addition to usual demographics data like age, gender and geographic location, a friendship structure between voters and the temporal dynamics of their activity during the voting process. Using a Facebook application we collected friendship relationships, demographics and votes of over ten thousand users on the referendum on the definition of marriage in Croatia held on 1st of December 2013. We also collected data on online news articles mentioning our application. Publication of these articles align closely with large peaks of voting activity, indicating that these external events have a crucial influence in engaging the voters. Also, existence of strongly connected friendship communities where majority of users vote during short time period, and the fact that majority of users in general tend to friend users that voted the same suggest that peer influence also has its role in engaging the voters. As we are not able to track activity of our users at all times, and we do not know their motivations for expressing their votes through our application, the question is whether we can infer peer and external influence using friendship network of users and the times of their voting. We propose a new method for estimation of magnitude of peer and external influence in friendship network and demonstrate its validity on both simulated and actual data.",
keywords = "information spreading in networks;social networks;temporal networks",
title = "{M}odeling peer and external influence in online social networks",
url = "http://arxiv.org/abs/1610.08262",
year = "2016",
}
@article{mureddu2016islanding,
author = "Mario Mureddu and Guido Caldarelli and Alfonso Damiano and Antonio Scala and Hildegard Meyer-Ortmanns",
doi = "10.1038/srep34797",
issn = "2045-2322",
journal = "Scientific Reports",
pages = "34797",
publisher = "Nature Publishing Group",
title = "{I}slanding the power grid on the transmission level: less connections for more security",
url = "http://www.nature.com/articles/srep34797",
volume = "6",
year = "2016",
}
@article{mertzios2016stably,
author = "George B Mertzios and Sotiris E Nikoletseas and Christoforos L Raptopoulos and Paul G Spirakis",
number = "69",
pages = "1--13",
title = "{S}tably {C}omputing {O}rder {S}tatistics with {A}rithmetic {P}opulation {P}rotocols â",
year = "2016",
}
@article{mertzios2016determining,
author = "George B. Mertzios and Sotiris E. Nikoletseas and Christoforos L. Raptopoulos and Paul G. Spirakis",
abstract = "We study here the problem of determining the majority type in an arbitrary connected network, each vertex of which has initially two possible types. The vertices may have a few additional possible states and can interact in pairs only if they share an edge. Any (population) protocol is required to stabilize in the initial majority. We first present and analyze a protocol with 4 states per vertex that always computes the initial majority value, under any fair scheduler. As we prove, this protocol is optimal, in the sense that there is no population protocol that always computes majority with fewer than 4 states per vertex. However this does not rule out the existence of a protocol with 3 states per vertex that is correct with high probability. To this end, we examine a very natural majority protocol with 3 states per vertex, introduced in [Angluin et al. 2008] where its performance has been analyzed for the clique graph. We study the performance of this protocol in arbitrary networks. We prove that, when the two initial states are put uniformly at random on the vertices, this protocol converges to the initial majority with probability higher than the probability of converging to the initial minority. In contrast, we present an infinite family of graphs, on which the protocol can fail whp, even when the difference between the initial majority and the initial minority is {\$}n - \backslashTheta(\backslashln{\{}n{\}}){\$}. We also present another infinite family of graphs in which the protocol of Angluin et al. takes an expected exponential time to converge. These two negative results build upon a very positive result concerning the robustness of the protocol on the clique. Surprisingly, the resistance of the clique to failure causes the failure in general graphs. Our techniques use new domination and coupling arguments for suitably defined processes whose dynamics capture the antagonism between the states involved.",
doi = "10.1007/s00446-016-0277-8",
isbn = "9783662439470",
issn = "01782770",
journal = "Distributed Computing",
keywords = "Coupling;Majority in networks;Population protocol;Probabilistic scheduler",
pages = "1--16",
title = "{D}etermining majority in networks with local interactions and very small local memory",
year = "2016",
}
@article{michail2016simple,
author = "Othon Michail and Paul G. Spirakis",
abstract = "In this work, we study protocols so that populations of distributed processes can construct networks. In order to highlight the basic principles of distributed network construction we keep the model minimal in all respects. In particular, we assume finite-state processes that all begin from the same initial state and all execute the same protocol. Moreover, we assume pairwise interactions between the processes that are scheduled by a fair adversary. In order to allow processes to construct networks, we let them activate and deactivate their pairwise connections. When two processes interact, the protocol takes as input the states of the processes and the state of their connection and updates all of them. Initially all connections are inactive and the goal is for the processes, after interacting and activating/deactivating connections for a while, to end up with a desired stable network. We give protocols (optimal in some cases) and lower bounds for several basic network construction problems such as spanning line, spanning ring, spanning star, and regular network. The expected time to convergence of our protocols is analyzed under a uniform random, scheduler. Finally, we prove several universality results by presenting generic protocols that are capable of simulating a Turing Machine (TM) and exploiting it in order to construct a large class of networks. We additionally show how to partition the population into k supernodes, each being a line of log k nodes, for the largest such k. This amount of local memory is sufficient for the supernodes to obtain unique names and exploit their names and their memory to realize nontrivial constructions. Copyright is held by the owner/author(s). Publication rights licensed to ACM.",
doi = "10.1007/s00446-015-0257-4",
isbn = "9781450329446",
issn = "01782770",
journal = "Distributed Computing",
keywords = "Distributed network construction;Distributed protocol;Fairness;Homogeneous population;Interacting automata;Random schedule;Self-organization;Stabilization;Structure formation",
number = "3",
pages = "207--237",
publisher = "Springer Berlin Heidelberg",
title = "{S}imple and efficient local codes for distributed stable network construction",
url = ""http://dx.doi.org/10.1007/s00446-015-0257-4",
volume = "29",
year = "2016",
}
@article{michail2016traveling,
author = "Othon Michail and Paul G. Spirakis",
abstract = "In this work, we introduce the notion of time to some well-known combinatorial optimization problems. In particular, we study problems defined on temporal graphs. A temporal graph D=(V, A) may be viewed as a time-sequence G1, G2, . . ., Gl of static graphs over the same (static) set of nodes V. Each Gt=D(t)=(V, A(t)) is called the instance of D at time t and l is called the lifetime of D. Our main focus is on analogues of traveling salesman problems in temporal graphs. A sequence of time-labeled edges (e.g. a tour) is called temporal if its labels are strictly increasing. We begin by considering the problem of exploring the nodes of a temporal graph as soon as possible. In contrast to the positive results known for the static case, we prove that, it cannot be approximated within cn, for some constant c{\textgreater}0, in a special case of temporal graphs and within (2-??), for every constant ??{\textgreater}0, in another special case in which D(t) is strongly connected for all 1???t???l, both unless P=NP. We then study the temporal analogue of TSP(1, 2), abbreviated TTSP(1, 2), where, for all 1???t???l, D(t) is a complete weighted graph with edge-costs from {\{}1, 2{\}} and the cost of an edge may vary from instance to instance. The goal is to find a minimum cost temporal TSP tour. We give several polynomial-time approximation algorithms for TTSP(1, 2). Our best approximation is (1.7+??) for the generic TTSP(1, 2) and (13/8+??) for its interesting special case in which the lifetime of the temporal graph is restricted to n. In the way, we also introduce temporal versions of other fundamental combinatorial optimization problems, for which we obtain polynomial-time approximation algorithms and hardness results.",
doi = "10.1016/j.tcs.2016.04.006",
isbn = "9783662444641",
issn = "03043975",
journal = "Theoretical Computer Science",
keywords = "Approximation algorithm;Dynamic network;Exploration;Hardness result;TSP with costs one and two;Temporal matching",
pages = "1--23",
publisher = "Elsevier B.V.",
title = "{T}raveling salesman problems in temporal graphs",
url = "http://dx.doi.org/10.1016/j.tcs.2016.04.006",
volume = "634",
year = "2016",
}
@article{mihelcic2016interset,
author = "Matej Mihelcic and Tomsilav Smuc",
abstract = "Ordering and ranking items of different types (observations, web pages, etc.) are important tasks in various applications, such as query processing and scientific data mining. We consider different problems of inferring total or partial orders from data, with special emphasis on applications to the seriation problem in paleontology. Seriation can be viewed as the task of ordering rows of a 0-1 matrix so that certain conditions hold. We review different approaches to this task, including spectral ordering methods, techniques for finding partial orders, and probabilistic models using MCMC methods. Joint work with Antti Ukkonen, Aris Gionis, Mikael Fortelius, Kai Puolam{\"a}ki, and Jukka Jernvall.",
doi = "10.1007/978-3-540-88411-8",
isbn = "978-3-540-88410-1",
issn = "0302-9743",
journal = "LNAI",
keywords = "interactive exploration;knowledge discovery;tion set",
pages = "35--50",
title = "{I}nter{S}et: {I}nteractive {R}edescription {S}et {E}xploration",
url = "http://www.springerlink.com/content/6014730541hr7236",
volume = "9956",
year = "2016",
}
@article{mozetic2016multilingual,
author = "Igor Mozeti{\v{c}} and Miha Gr{\v{c}}ar and Jasmina Smailovi{\'{c}}",
abstract = "What are the limits of automated Twitter sentiment classification? We analyze a large set of manually labeled tweets in different languages, use them as training data, and construct automated classification models. It turns out that the quality of classification models depends much more on the quality and size of training data than on the type of the model trained. Experimental results indicate that there is no statistically significant difference between the performance of the top classification models. We quantify the quality of training data by applying various annotator agreement measures, and identify the weakest points of different datasets. We show that the model performance approaches the inter-annotator agreement when the size of the training set is sufficiently large. However, it is crucial to regularly monitor the self-and inter-annotator agreements since this improves the training datasets and con-sequently the model performance. Finally, we show that there is strong evidence that humans perceive the sentiment classes (negative, neutral, and positive) as ordered.",
doi = "10.1371/journal.pone.0155036",
journal = "PLoS ONE",
number = "5",
pages = "e0155036",
title = "{M}ultilingual {T}witter {S}entiment {C}lassification: {T}he {R}ole of {H}uman {A}nnotators",
url = "http://dx.doi.org/10.1371/journal.pone.0155036",
volume = "11",
year = "2016",
}
@techreport{maecker2016online,
author = "Alexander Maecker and Manuel Malatyali",
booktitle = "arxiv:submit/1705819",
number = "317532",
pages = "1--10",
title = "{O}nline {T}op- k -{P}osition {M}onitoring of {D}istributed {D}ata {S}treams",
year = "2016",
}
@article{maecker2016competitive,
author = "Alexander Maecker and Manuel Malatyali and Friedhelm Meyer Auf Der Heide",
abstract = "Consider the continuous distributed monitoring model in which {\$}n{\$} distributed nodes, receiving individual data streams, are connected to a designated server. The server is asked to continuously monitor a function defined over the values observed across all streams while minimizing the communication. We study a variant in which the server is equipped with a broadcast channel and is supposed to keep track of an approximation of the set of nodes currently observing the {\$}k{\$} largest values. Such an approximate set is exact except for some imprecision in an {\$}\backslashvarepsilon{\$}-neighborhood of the {\$}k{\$}-th largest value. This approximation of the Top-{\$}k{\$}-Position Monitoring Problem is of interest in cases where marginal changes (e.g.$\backslash$ due to noise) in observed values can be ignored so that monitoring an approximation is sufficient and can reduce communication. This paper extends our results from [IPDPS'15], where we have developed a filter-based online algorithm for the (exact) Top-k-Position Monitoring Problem. There we have presented a competitive analysis of our algorithm against an offline adversary that also is restricted to filter-based algorithms. Our new algorithms as well as their analyses use new methods. We analyze their competitiveness against adversaries that use both exact and approximate filter-based algorithms, and observe severe differences between the respective powers of these adversaries.",
doi = "10.1109/IPDPS.2016.91",
isbn = "9781509021406",
journal = "Proceedings - 2016 IEEE 30th International Parallel and Distributed Processing Symposium, IPDPS 2016",
keywords = "Approximation;Continuous computation;Distributed monitoring;Online data streams;Top-k;Tracking",
number = "317532",
pages = "700--709",
title = "{O}n {C}ompetitive {A}lgorithms for {A}pproximations of {T}op-k-{P}osition {M}onitoring of {D}istributed {S}treams",
year = "2016",
}
@article{Magalich2016science,
author = "A Magalich and V Palchykov and V Gemmetto and D Garlaschelli and A Boyarsky and A Martini and A Cardillo and A Constantin and O Ruchayskiy and P De Los Rios and K Aberer",
title = "{S}cience{WISE} : {T}opic {M}odeling over {S}cientific {L}iterature {N}etworks",
year = "2016",
}
@article{majdandzic2016multiple,
author = "Antonio Majdandzic and Lidia A Braunstein and Chester Curme and Irena Vodenska and Sary Levy-Carciente and H {Eugene Stanley} and Shlomo Havlin",
abstract = "Systems composed of many interacting dynamical networks-such as the human body with its biological networks or the global economic network consisting of regional clusters-often exhibit complicated collective dynamics. Three fundamental processes that are typically present are failure, damage spread and recovery. Here we develop a model for such systems and find a very rich phase diagram that becomes increasingly more complex as the number of interacting networks increases. In the simplest example of two interacting networks we find two critical points, four triple points, ten allowed transitions and two 'forbidden' transitions, as well as complex hysteresis loops. Remarkably, we find that triple points play the dominant role in constructing the optimal repairing strategy in damaged interacting systems. To test our model, we analyse an example of real interacting financial networks and find evidence of rapid dynamical transitions between well-defined states, in agreement with the predictions of our model.",
doi = "10.1038/ncomms10850",
isbn = "9781467367592",
issn = "2041-1723",
journal = "Nature communications",
pages = "10850",
publisher = "Nature Publishing Group",
title = "{M}ultiple tipping points and optimal repairing in interacting networks.",
url = "http://www.nature.com/ncomms/2016/160301/ncomms10850/full/ncomms10850.html",
volume = "7",
year = "2016",
}
@article{mastrandrea2016how,
author = "Rossana Mastrandrea and Alain Barrat",
doi = "10.1371/journal.pcbi.1005002",
issn = "15537358",
journal = "PLoS Computational Biology",
number = "6",
pages = "1--19",
title = "{H}ow to {E}stimate {E}pidemic {R}isk from {I}ncomplete {C}ontact {D}iaries {D}ata?",
volume = "12",
year = "2016",
}
@article{krause2016hidden,
author = "Sebastian M. Krause",
doi = "10.1103/PhysRevX.6.041022",
issn = "2160-3308",
journal = "Physical Review X",
keywords = "complex systems;statistical physics",
number = "4",
pages = "041022",
title = "{H}idden {C}onnectivity in {N}etworks with {V}ulnerable {C}lasses of {N}odes",
volume = "6",
year = "2016",
}
@techreport{leduc2016systemic,
author = "Matt V. Leduc and Sebastian Poledna and Stefan Thurner",
abstract = "We study insolvency cascades in an interbank system when banks are allowed to insure their loans with credit default swaps (CDS) sold by other banks. We show that, by properly shifting financial exposures from one institution to another, a CDS market can be designed to rewire the network of interbank exposures in a way that makes it more resilient to insolvency cascades. A regulator can use information about the topology of the interbank network to devise a systemic insurance surcharge that is added to the CDS spread. CDS contracts are thus effectively penalized according to how much they contribute to increasing systemic risk. CDS contracts that decrease systemic risk remain untaxed. We simulate this regulated CDS market using an agent-based model (CRISIS macro-financial model) and we demonstrate that it leads to an interbank system that is more resilient to insolvency cascades.",
keywords = "agent-based mod-;credit default swaps;debtrank;els;interbank systems;multiplex networks;systemic risk",
pages = "18",
title = "{S}ystemic {R}isk {M}anagement in {F}inancial {N}etworks with {C}redit {D}efault {S}waps",
url = "http://arxiv.org/abs/1601.02156",
year = "2016",
}
@article{lee2016hybrid,
author = "Deokjae Lee and S. Choi and M. Stippinger and J. Kert{\'e}sz and B. Kahng",
abstract = "Interdependent networks are more fragile under random attacks than simplex networks, because interlayer dependencies lead to cascading failures and finally to a sudden collapse. This is a hybrid phase transition (HPT), meaning that at the transition point the order parameter has a jump but there are also critical phenomena related to it. Here we study these phenomena on the Erd$\backslash$H{\{}o{\}}s--R$\backslash$'enyi and the two dimensional interdependent networks and show that the hybrid percolation transition exhibits two kinds of critical behaviors: divergence of the fluctuations of the order parameter and power-law size distribution of finite avalanches at a transition point. At the transition point, avalanches of infinite size occur thus the avalanche statistics also has the nature of a HPT. The exponent {\$}\backslashbeta{\_}m{\$} of the order parameter is {\$}1/2{\$} under general conditions, while the value of the exponent {\$}\backslashgamma{\_}m{\$} characterizing the fluctuations of the order parameter depends on the system. The critical behavior of the finite avalanches can be described by another set of exponents, {\$}\backslashbeta{\_}a{\$} and {\$}\backslashgamma{\_}a{\$}. These two critical behaviors are coupled by a scaling law: {\$}1-\backslashbeta{\_}m=\backslashgamma{\_}a{\$}.",
doi = "10.1103/PhysRevE.93.042109",
issn = "15502376",
journal = "Physical Review E - Statistical, Nonlinear, and Soft Matter Physics",
number = "4",
pages = "1--11",
title = "{H}ybrid phase transition into an absorbing state: {P}ercolation and avalanches",
volume = "93",
year = "2016",
}
@article{li2016fundamental,
author = "Aming Li and Sean P. Cornelius and Yang-Yu Liu and Long Wang and Albert-L{\'a}szl{\'o} Barab{\'a}si",
abstract = "Despite the traditional focus of network science on static networks, most networked systems of scientific interest are characterized by temporal links. By disrupting the paths, link temporality has been shown to frustrate many dynamical processes on networks, from information spreading to accessibility. Considering the ubiquity of temporal networks in nature, we must ask: Are there any advantages of the networks' temporality? Here we develop an analytical framework to explore the control properties of temporal networks, arriving at the counterintuitive conclusion that temporal networks, compared to their static (i.e. aggregated) counterparts, reach controllability faster, demand orders of magnitude less control energy, and the control trajectories, through which the system reaches its final states, are significantly more compact than those characterizing their static counterparts. The combination of analytical, numerical and empirical results demonstrates that temporality ensures a degree of flexibility that would be unattainable in static networks, significantly enhancing our ability to control them.",
journal = "arXiv",
pages = "1--45",
title = "{T}he fundamental advantages of temporal networks",
url = "http://arxiv.org/abs/1607.06168",
year = "2016",
}
@article{lopes2016synchronization,
author = "M. A. Lopes and E. M. Lopes and S. Yoon and J. F. F. Mendes and A. V. Goltsev",
abstract = "We study the impact of random pinning fields on the emergence of synchrony in the Kuramoto model on complete graphs and uncorrelated random complex networks. We consider random fields with uniformly distributed directions and homogeneous and heterogeneous (Gaussian) field magnitude distribution. In our analysis we apply the Ott-Antonsen method and the annealed-network approximation to find the critical behavior of the order parameter. In the case of homogeneous fields, we find a tricritical point above which a second-order phase transition gives place to a first-order phase transition when the network is either fully connected, or scale-free with the degree exponent {\$}\backslashgamma{\textgreater}5{\$}. Interestingly, for scale-free networks with {\$}2{\textless}\backslashgamma \backslashleq 5{\$}, the phase transition is of second-order at any field magnitude, except for degree distributions with {\$}\backslashgamma=3{\$} when the transition is of infinite order at {\$}K{\_}c=0{\$} independently on the random fields. Contrarily to the Ising model, even strong Gaussian random fields do not suppress the second-order phase transition in both complete graphs and scale-free networks though the fields increase the critical coupling for {\$}\backslashgamma {\textgreater} 3{\$}. Our simulations support these analytical results.",
doi = "10.1103/PhysRevE.94.012308",
issn = "15502376",
journal = "Physical Review E",
pages = "012308",
title = "{S}ynchronization in the random field {K}uramoto model on complex networks",
url = "http://arxiv.org/abs/1605.04733",
volume = "94",
year = "2016",
}
@article{jo2016static,
author = "Hang-Hyun Jo and Yohsuke Murase and J{\'a}nos T{\"o}r{\"o}k and J{\'a}nos Kert{\'e}sz and Kimmo Kaski",
abstract = "The past analyses of available datasets for social networks have given rise to a number of empirical findings that cover only some parts or aspects of the society, but leave the structure of the whole social network largely unexplored due to lack of even more comprehensive datasets. In order to model the whole social network, we assume that some properties of the network are reflected in empirical findings that are commonly featured as $\backslash$emph{\{}stylized facts{\}} of social networks, such as broad distributions of network quantities, existence of communities, assortative mixing, and intensity-topology correlations. Several models have been studied to generate the stylized facts, but most of them focus on the processes or mechanisms behind stylized facts. In this paper, we take an alternative approach by devising a static model for the whole social network, for which we randomly assign a number of communities to a given set of isolated nodes using a few assumptions, i.e., the community size is heterogeneous, and larger communities are assigned with smaller link density and smaller characteristic link weight. With these assumptions, we are able to generate realistic social networks that show most stylized facts for a wide range of parameters. This in turn can explain why the stylized facts are so commonly observed. We also obtain analytic results for various network quantities that turn out to be comparable with the numerical results. In contrast to the dynamical generative models, our static model is simple to implement and easily scalable. Hence, it can be used as a reference system for further applications.",
journal = "arxiv:1611.03664",
pages = "1--12",
title = "{A} {S}tatic {M}odel for {S}tylized {F}acts in {S}ocial {N}etworks",
url = "http://arxiv.org/abs/1611.03664",
year = "2016",
}
@article{kertesz2016multiplex,
author = "Janos Kertesz and Janos Torok and Yohsuke Murase and Hang-Hyun Jo and Kimmo Kaski",
abstract = "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.",
pages = "1--24",
title = "{M}ultiplex {M}odeling of the {S}ociety",
url = "http://arxiv.org/abs/1609.08381",
year = "2016",
}
@article{kiti2016quantifying,
author = "Moses C. Kiti and Michele Tizzoni and Timothy M. Kinyanjui and Dorothy C. Koech and Patrick K. Munywoki and Milosch Meriac and Luca Cappa and Andr{\'e} Panisson and Alain Barrat and Ciro Cattuto and D. James Nokes",
doi = "10.1140/epjds/s13688-016-0084-2",
issn = "21931127",
journal = "EPJ Data Science",
keywords = "contact networks;contact patterns;households;infectious disease control;respiratory infections;wearable proximity sensors",
number = "1",
publisher = "Kiti et al.",
title = "{Q}uantifying social contacts in a household setting of rural {K}enya using wearable proximity sensors",
url = "http://dx.doi.org/10.1140/epjds/s13688-016-0084-2",
volume = "5",
year = "2016",
}
@article{klimek2016dynamical,
author = "Peter Klimek and Marina Diakonova and Victor Eguiluz and Maxi San Miguel and Stefan Thurner",
abstract = "Social structures emerge as a result of individuals managing a variety of different of social relationships. Societies can be represented as highly structured dynamic multiplex networks. Here we study the dynamical origins of the specific community structures of a large-scale social multiplex network of a human society that interacts in a virtual world of a massive multiplayer online game. There we find substantial differences in the community structures of different social actions, represented by the various network layers in the multiplex. Community size distributions are either similar to a power-law or appear to be centered around a size of 50 individuals. To understand these observations we propose a voter model that is built around the principle of triadic closure. It explicitly models the co-evolution of node- and link-dynamics across different layers of the multiplex. Depending on link- and node fluctuation rates, the model exhibits an anomalous shattered fragmentation transition, where one layer fragments from one large component into many small components. The observed community size distributions are in good agreement with the predicted fragmentation in the model. We show that the empirical pairwise similarities of network layers, in terms of link overlap and degree correlations, practically coincide with the model. This suggests that several detailed features of the fragmentation in societies can be traced back to the triadic closure processes.",
doi = "10.1088/1367-2630/18/8/083045",
issn = "1367-2630",
journal = "New Journal of Physics",
keywords = "community detection;multiplex network;social networks;voter model",
number = "8",
pages = "1--8",
publisher = "IOP Publishing",
title = "{D}ynamical origins of the community structure of multi-layer societies",
url = "http://arxiv.org/abs/1601.01576",
volume = "18",
year = "2016",
}
@article{klimek2016successful,
author = "Peter Klimek and Aleksandar {S. Jovanovic} and Rainer Egloff and Reto Schneider",
abstract = "In this work we address the challenge of how to identify those documents from a given set of texts that are most likely to have substantial impact in the future. To this end we develop a purely content-based methodology in order to rank a given set of documents, for example abstracts of scientific publications, according to their potential to generate impact as measured by the numbers of citations that the articles will receive in the future. We construct a bipartite network consisting of documents that are linked to keywords and terms that they contain. We study recursive centrality measures for such networks that quantify how many different terms a document contains and how these terms are related to each other. From this we derive a novel indicatorâ€”document centralityâ€”that is shown to be highly predictive of citation impact in six different case studies. We compare these results to findings from a multivariable regression model and from conventional network-based centrality measures to show that document centrality indeed offers a comparably high performance in identifying those articles that contain a large number of high-impact keywords. Our findings suggest that articles which conform to the mainstream within a given research field tend to receive higher numbers of citations than highly original and innovative articles.",
doi = "10.1007/s11192-016-1926-1",
issn = "15882861",
journal = "Scientometrics",
keywords = "Bipartite networks;Citation impact prediction;Network theory",
number = "3",
pages = "1265--1282",
publisher = "Springer Netherlands",
title = "{S}uccessful fish go with the flow: citation impact prediction based on centrality measures for term-document networks",
url = ""http://dx.doi.org/10.1007/s11192-016-1926-1",
volume = "107",
year = "2016",
}
@article{hric2016network,
author = "Darko Hric and Tiago P. Peixoto and Santo Fortunato",
abstract = "The empirical validation of community detection methods is often based on available annotations on the nodes that serve as putative indicators of the large-scale network structure. Most often, the suitability of the annotations as topological descriptors itself is not assessed, and without this it is not possible to ultimately distinguish between actual shortcomings of the community detection algorithms on one hand, and the incompleteness, inaccuracy or structured nature of the data annotations themselves on the other. In this work we present a principled method to access both aspects simultaneously. We construct a joint generative model for the data and metadata, and a non-parametric Bayesian framework to infer its parameters from annotated datasets. We assess the quality of the metadata not according to its direct alignment with the network communities, but rather in its capacity to predict the placement of edges in the network. We also show how this feature can be used to predict the connections to missing nodes when only the metadata is available. By investigating a wide range of datasets, we show that while there are seldom exact agreements between metadata tokens and the inferred data groups, the metadata is often informative of the network structure nevertheless, and can improve the prediction of missing nodes. This shows that the method uncovers meaningful patterns in both the data and metadata, without requiring or expecting a perfect agreement between the two.",
doi = "10.1109/NTMS.2009.5384673 10.1007/978-90-481-3662-9_77\n 10.1007/978-90-481-3662-9_73",
issn = "2160-3308",
journal = "Physical Review X",
keywords = "complex systems;statistical physics",
pages = "031038",
title = "{N}etwork structure, metadata and the prediction of missing nodes",
url = "http://arxiv.org/abs/1604.00255",
volume = "6",
year = "2016",
}
@article{gleeson2016effects,
author = "James P. Gleeson and Kevin P. O'Sullivan and Raquel A. Ba{\~n}os and Yamir Moreno",
abstract = "Online social media has greatly affected the way in which we communicate with each other. However, little is known about what fundamental mechanisms drive dynamical information flow in online social systems. Here, we introduce a generative model for online sharing behavior that is analytically tractable and that can reproduce several characteristics of empirical micro-blogging data on hashtag usage, such as (time-dependent) heavy-tailed distributions of meme popularity. The presented framework constitutes a null model for social spreading phenomena that, in contrast to purely empirical studies or simulation-based models, clearly distinguishes the roles of two distinct factors affecting meme popularity: the memory time of users and the connectivity structure of the social network.",
doi = "10.1103/PhysRevX.6.021019",
issn = "2160-3308",
journal = "Physical Review X",
keywords = "complex systems",
number = "2",
pages = "021019",
title = "{E}ffects of {N}etwork {S}tructure, {C}ompetition and {M}emory {T}ime on {S}ocial {S}preading {P}henomena",
url = "http://link.aps.org/doi/10.1103/PhysRevX.6.021019",
volume = "6",
year = "2016",
}
@techreport{gmyr2015self,
author = "Robert Gmyr and Jonas Lef{\`e}vre and Christian Scheideler",
keywords = "metric graph;overlay network;self-stabilizing algorithms",
title = "{S}elf-stabilizing {M}etric {G}raphs",
year = "2016",
}
@article{goel2016reservation,
author = "Gagan Goel and Stefano Leonardi and Vahab Mirrokni and Renato Paes-leme",
keywords = "142;2016;4230;and phrases reservation markets;auction;clinching;digital object identifier 10;envy-free allocations;icalp;internet advertising;lipics;two-sided markets",
number = "142",
pages = "1--14",
title = "{R}eservation {E}xchange {M}arkets for {I}nternet",
year = "2016",
}
@article{gomez-Gardenes2016layer,
author = "Jesus Gomez-Gardenes and M {De Domenico} and G Guti{\'e}rrez and A Arenas and S G{\'o}mez",
journal = "Phylosophical Transactions of the Royal Society A",
keywords = "complexity;statistical physics",
pages = "20150117",
title = "{L}ayer â€“ layer competition in multiplex complex networks {S}ubject {A}reas",
volume = "373",
year = "2016",
}