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  • Multiplex networks reveal geographic constraints on illicit wildlife trafficking
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2020-03-31
    Felber J. Arroyave, Alexander M. Petersen, Jeffrey Jenkins, Rafael Hurtado

    Abstract Illicit wildlife trafficking poses a threat to the conservation of species and ecosystems, and represents a fundamental source of biodiversity loss, alongside climate change and large-scale land degradation. Despite the seriousness of this issue, little is known about various socio-cultural demand sources underlying trafficking networks, for example the forthright consumption of endangered

    更新日期:2020-03-31
  • On modeling blockchain-enabled economic networks as stochastic dynamical systems
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2020-03-19
    Zixuan Zhang, Michael Zargham, Victor M. Preciado

    Abstract Blockchain networks have attracted tremendous attention for creating cryptocurrencies and decentralized economies built on peer-to-peer protocols. However, the complex nature of the dynamics and feedback mechanisms within these economic networks has rendered it difficult to reason about the growth and evolution of these networks. Hence, proper mathematical frameworks to model and analyze the

    更新日期:2020-03-19
  • Evolving network representation learning based on random walks
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2020-03-18
    Farzaneh Heidari, Manos Papagelis

    Abstract Large-scale network mining and analysis is key to revealing the underlying dynamics of networks, not easily observable before. Lately, there is a fast-growing interest in learning low-dimensional continuous representations of networks that can be utilized to perform highly accurate and scalable graph mining tasks. A family of these methods is based on performing random walks on a network to

    更新日期:2020-03-19
  • Using correlated stochastic differential equations to forecast cryptocurrency rates and social media activities
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2020-03-11
    Stephen Dipple, Abhishek Choudhary, James Flamino, Boleslaw K. Szymanski, G. Korniss

    Abstract The growing interconnectivity of socio-economic systems requires one to treat multiple relevant social and economic variables simultaneously as parts of a strongly interacting complex system. Here, we analyze and exploit correlations between the price fluctuations of selected cryptocurrencies and social media activities, and develop a predictive framework using noise-correlated stochastic

    更新日期:2020-03-12
  • Security through block vault in a blockchain enabled federated cloud framework
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2020-02-27
    Olumide Malomo, Danda Rawat, Moses Garuba

    Abstract The survivability of any organization in the event of disaster or attack could greatly depend on its offsite data recovery. But which provider could offer secure and resilient cyber security protection to offsite data is a major problem for individuals, businesses and organizations. In recent times, cyber-attacks are strategic and tactical. Adversaries are advanced with capability to access

    更新日期:2020-02-28
  • Making communities show respect for order
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2020-02-21
    Vaiva Vasiliauskaite, Tim S. Evans

    Abstract In this work we give a community detection algorithm in which the communities both respects the intrinsic order of a directed acyclic graph and also finds similar nodes. We take inspiration from classic similarity measures of bibliometrics, used to assess how similar two publications are, based on their relative citation patterns. We study the algorithm’s performance and antichain properties

    更新日期:2020-02-21
  • Corruption and complexity: a scientific framework for the analysis of corruption networks
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2020-02-19
    Issa Luna-Pla, José R. Nicolás-Carlock

    Abstract According to United Nations, corruption is a systemic and adaptive phenomenon that requires comprehensive and multidisciplinary approaches for its effective prevention and combat. However, traditional approaches lack the analytical tools to handle the structural and dynamical aspects that characterize modern social, political and technological systems where corruption takes place. On this

    更新日期:2020-02-19
  • Partial correlation financial networks
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2020-02-05
    Tristan Millington, Mahesan Niranjan

    Abstract Correlation networks have been a popular way of inferring a financial network due to the simplicity of construction and the ease of interpretability. However two variables which share a common cause can be correlated, leading to the inference of spurious relationships. To solve this we can use partial correlation. In this paper we construct both correlation and partial correlation networks

    更新日期:2020-02-06
  • Online reactions to the 2017 ‘Unite the right’ rally in Charlottesville: measuring polarization in Twitter networks using media followership
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2020-01-31
    Joseph H. Tien, Marisa C. Eisenberg, Sarah T. Cherng, Mason A. Porter

    Abstract Network analysis of social media provides an important new lens on politics, communication, and their interactions. This lens is particularly prominent in fast-moving events, such as conversations and action in political rallies and the use of social media by extremist groups to spread their message. We study the Twitter conversation following the August 2017 ‘Unite the Right’ rally in Charlottesville

    更新日期:2020-01-31
  • Correction to: The weakness of weak ties for novel information diffusion
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2020-01-30
    Jennifer M. Larson

    Following publication of the original article (Larson Applied Network Science 2017), the author reported to publish a brief corrigendum in the original article;

    更新日期:2020-01-31
  • Annotated hypergraphs: models and applications
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2020-01-30
    Philip Chodrow, Andrew Mellor

    Abstract Hypergraphs offer a natural modeling language for studying polyadic interactions between sets of entities. Many polyadic interactions are asymmetric, with nodes playing distinctive roles. In an academic collaboration network, for example, the order of authors on a paper often reflects the nature of their contributions to the completed work. To model these networks, we introduce annotated hypergraphs

    更新日期:2020-01-31
  • Social and economic flows across multimodal transportation networks in the Greater Tokyo Area
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2020-01-22
    Aaron Bramson, Megumi Hori, Bingran Zha, Hirohisa Inamoto

    Abstract We model the flow of human capital and resources across multimodal transportation networks throughout the Greater Tokyo Area. Our transportation networks include trains, buses, and roads integrated with a walking network among a geographically grounded hexagonal grid and connecting nodes of different modes. The hexagonal grid holds data on both the working population and number of jobs from

    更新日期:2020-01-23
  • A survey on graph kernels
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2020-01-14
    Nils M. Kriege, Fredrik D. Johansson, Christopher Morris

    Abstract Graph kernels have become an established and widely-used technique for solving classification tasks on graphs. This survey gives a comprehensive overview of techniques for kernel-based graph classification developed in the past 15 years. We describe and categorize graph kernels based on properties inherent to their design, such as the nature of their extracted graph features, their method

    更新日期:2020-01-15
  • Correction to: Mobile phone data reveals the importance of pre-disaster inter-city social ties for recovery after Hurricane Maria
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2020-01-09
    Takahiro Yabe, Satish V. Ukkusuri, P. Suresh C. Rao

    Following publication of the original article [1], the author reported to remove the name from the acknowledgements in the original article.

    更新日期:2020-01-09
  • Joint embedding of structure and features via graph convolutional networks
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2020-01-09
    Sébastien Lerique, Jacob Levy Abitbol, Márton Karsai

    The creation of social ties is largely determined by the entangled effects of people’s similarities in terms of individual characters and friends. However, feature and structural characters of people usually appear to be correlated, making it difficult to determine which has greater responsibility in the formation of the emergent network structure. We propose AN2VEC, a node embedding method which ultimately

    更新日期:2020-01-09
  • Graph-based data clustering via multiscale community detection
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2020-01-08
    Zijing Liu, Mauricio Barahona

    Abstract We present a graph-theoretical approach to data clustering, which combines the creation of a graph from the data with Markov Stability, a multiscale community detection framework. We show how the multiscale capabilities of the method allow the estimation of the number of clusters, as well as alleviating the sensitivity to the parameters in graph construction. We use both synthetic and benchmark

    更新日期:2020-01-08
  • Centrality and shortest path length measures for the functional analysis of urban drainage networks
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2020-01-02
    Julian D. Reyes-Silva, Jonatan Zischg, Christopher Klinkhamer, P. Suresh C. Rao, Robert Sitzenfrei, Peter Krebs

    The objective of this research is to evaluate whether complex dynamics of urban drainage networks (UDNs) can be expressed in terms of their structure, i.e. topological characteristics. The present study focuses on the application of topological measures for describing the transport and collection functions of UDNs, using eight subnetworks of the Dresden sewer network as study cases. All UDNs are considered

    更新日期:2020-01-02
  • Quantitative analysis of cryptocurrencies transaction graph
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-12-30
    Amir Pasha Motamed, Behnam Bahrak

    Abstract Cryptocurrencies as a new way of transferring assets and securing financial transactions have gained popularity in recent years. Transactions in cryptocurrencies are publicly available, hence, statistical studies on different aspects of these currencies are possible. However, previous statistical analysis on cryptocurrencies transactions have been very limited and mostly devoted to Bitcoin

    更新日期:2019-12-31
  • Managing large distributed dynamic graphs for smart city network applications
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-12-30
    Nadav Voloch, Noa Voloch - Bloch, Yair Zadok

    Smart cities and traffic applications can be modelled by dynamic graphs for which vertices or edges can be added, removed or change their properties. In the smart city or traffic monitoring problem, we wish to detect if a city dynamic graph maintains a certain local or global property. Monitoring city large dynamic graphs, is even more complicated. To treat the monitoring problem efficiently we divide

    更新日期:2019-12-30
  • The time varying network of urban space uses in Milan
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-12-30
    Alba Bernini, Amadou Lamine Toure, Renato Casagrandi

    Abstract In a metropolis, people movements design intricate patterns that change on very short temporal scales. Population mobility obviously is not random, but driven by the land uses of the city. Such an urban ecosystem can interestingly be explored by integrating the spatial analysis of land uses (through ecological indicators commonly used to characterize natural environments) with the temporal

    更新日期:2019-12-30
  • Learning versus optimal intervention in random Boolean networks
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-12-30
    Matthew R. Karlsen, Sotiris K. Moschoyiannis, Vlad B. Georgiev

    Random Boolean Networks (RBNs) are an arguably simple model which can be used to express rather complex behaviour, and have been applied in various domains. RBNs may be controlled using rule-based machine learning, specifically through the use of a learning classifier system (LCS) – an eXtended Classifier System (XCS) can evolve a set of condition-action rules that direct an RBN from any state to a

    更新日期:2019-12-30
  • Dynamics of crime activities in the network of city community areas
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-12-26
    Xiang Niu, Amr Elsisy, Noemi Derzsy, Boleslaw K. Szymanski

    Understanding criminal activities, their structure and dynamics are fundamental for designing tools for crime prediction that can also guide crime prevention. Here, we study crimes committed in city community areas based on police crime reports and demographic data for the City of Chicago collected over 16 consecutive years. Our goal is to understand how the network of city community areas shapes dynamics

    更新日期:2019-12-27
  • Country centrality in the international multiplex network
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-12-26
    Giovanni Bonaccorsi, Massimo Riccaboni, Giorgio Fagiolo, Gianluca Santoni

    Abstract In this work we introduce and analyze a new and comprehensive multilayer dataset covering a wide spectrum of international relationships between coutries. We select two cross sections of the dataset corresponding to years 2003 and 2010 with 19 layers and 112 nodes to study the structure and evolution of the network. Country centrality is measured by the multiplex PageRank (MultiRank) and the

    更新日期:2019-12-27
  • A review of stochastic block models and extensions for graph clustering
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-12-23
    Clement Lee, Darren J. Wilkinson

    There have been rapid developments in model-based clustering of graphs, also known as block modelling, over the last ten years or so. We review different approaches and extensions proposed for different aspects in this area, such as the type of the graph, the clustering approach, the inference approach, and whether the number of groups is selected or estimated. We also review models that combine block

    更新日期:2019-12-25
  • Topological study of the convergence in the voter model
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-12-18
    Inés Caridi, Sergio Manterola, Viktoriya Semeshenko, Pablo Balenzuela

    The voter model has been widely studied due to its simple formulation and attainable theoretical treatment. The study of the “active links”, edges that connect nodes in different states, has been a key element in the analysis of the convergence of the model. Typically, the density of active links, ρ, is used to characterize the system when approaching to absorbing state. However, more information can

    更新日期:2019-12-19
  • On community structure in complex networks: challenges and opportunities
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-12-16
    Hocine Cherifi, Gergely Palla, Boleslaw K. Szymanski, Xiaoyan Lu

    Community structure is one of the most relevant features encountered in numerous real-world applications of networked systems. Despite the tremendous effort of a large interdisciplinary community of scientists working on this subject over the past few decades to characterize, model, and analyze communities, more investigations are needed in order to better understand the impact of community structure

    更新日期:2019-12-17
  • Commuting times and the mobilisation of skills in emergent cities
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-12-16
    Neave O’Clery, Rafael Prieto Curiel, Eduardo Lora

    Labour mobility within a large city or metropolitan area is a necessary condition for the optimal exploitation of agglomeration economies. We propose a method to establish which municipalities should be considered part of a metropolitan area based on labour market integration. In order to aggregate geographically proximate urban municipalities, we develop a network-based model that makes industry productivity

    更新日期:2019-12-17
  • Fact-checking strategies to limit urban legends spreading in a segregated society
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-12-04
    Marcella Tambuscio; Giancarlo Ruffo

    We propose a framework to study the spreading of urban legends, i.e., false stories that become persistent in a local popular culture, where social groups are naturally segregated by virtue of many (both mutable and immutable) attributes. The goal of this work is identifying and testing new strategies to restrain the dissemination of false information, focusing on the role of network polarization.

    更新日期:2019-12-04
  • Penalized inference of the hematopoietic cell differentiation network via high-dimensional clonal tracking
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-12-02
    Danilo Pellin; Luca Biasco; Alessandro Aiuti; Maria Clelia Di Serio; Ernst C. Wit

    Background During their lifespan, stem- or progenitor cells have the ability to differentiate into more committed cell lineages. Understanding this process can be key in treating certain diseases. However, up until now only limited information about the cell differentiation process is known. Aim The goal of this paper is to present a statistical framework able to describe the cell differentiation process

    更新日期:2019-12-02
  • Correction to: Detecting social media users based on pedestrian networks and neighborhood attributes: an observational study
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-11-29
    Victor H. Masias, Tobias Hecking, Fernando Crespo, H. Ulrich Hoppe

    Following publication of the original article [1], the author reported that figure 5 numbered correction was not implemented during the production process. The corrected figure can be found below.

    更新日期:2019-11-30
  • Modelling urban networks using Variational Autoencoders
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-11-29
    Kira Kempinska; Roberto Murcio

    A long-standing question for urban and regional planners pertains to the ability to describe urban patterns quantitatively. Cities’ transport infrastructure, particularly street networks, provides an invaluable source of information about the urban patterns generated by peoples’ movements and their interactions. With the increasing availability of street network datasets and the advancements in deep

    更新日期:2019-11-29
  • Py3plex toolkit for visualization and analysis of multilayer networks
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-10-29
    Blaž Škrlj, Jan Kralj, Nada Lavrač

    Complex networks are used as means for representing multimodal, real-life systems. With increasing amounts of data that lead to large multilayer networks consisting of different node and edge types, that can also be subject to temporal change, there is an increasing need for versatile visualization and analysis software. This work presents a lightweight Python library, Py3plex, which focuses on the

    更新日期:2019-11-28
  • Detecting social media users based on pedestrian networks and neighborhood attributes: an observational study
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-10-29
    Victor H. Masias, Tobias Hecking, Fernando Crespo, H. Ulrich Hoppe

    This paper proposes a methodological approach to explore the ability to detect social media users based on pedestrian networks and neighborhood attributes. We propose the use of a detection function belonging to the Spatial Capture–Recapture (SCR) which is a powerful analytical approach for detecting and estimating the abundance of biological populations. To test our approach, we created a set of proxy

    更新日期:2019-11-28
  • Local memory boosts label propagation for community detection
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-10-29
    Antonio Maria Fiscarelli, Matthias R. Brust, Grégoire Danoy, Pascal Bouvry

    The objective of a community detection algorithm is to group similar nodes that are more connected to each other than with the rest of the network. Several methods have been proposed but many are of high complexity and require global knowledge of the network, which makes them less suitable for large-scale networks. The Label Propagation Algorithm initially assigns a distinct label to each node that

    更新日期:2019-11-28
  • Inferring network properties based on the epidemic prevalence
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-10-29
    Long Ma, Qiang Liu, Piet Van Mieghem

    Dynamical processes running on different networks behave differently, which makes the reconstruction of the underlying network from dynamical observations possible. However, to what level of detail the network properties can be determined from incomplete measurements of the dynamical process is still an open question. In this paper, we focus on the problem of inferring the properties of the underlying

    更新日期:2019-11-28
  • How do urban mobility (geo)graph’s topological properties fill a map?
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-10-26
    Leonardo Bacelar Lima Santos, Luiz Max Carvalho, Wilson Seron, Flávio C. Coelho, Elbert E. Macau, Marcos G. Quiles, Antônio M. V. Monteiro

    Urban mobility data are important to areas ranging from traffic engineering to the analysis of outbreaks and disasters. In this paper, we study mobility data from a major Brazilian city from a geographical viewpoint using a Complex Network approach. The case study is based on intra-urban mobility data from the Metropolitan area of Rio de Janeiro (Brazil), presenting more than 480 spatial network nodes

    更新日期:2019-11-28
  • Gender and collaboration patterns in a temporal scientific authorship network
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-11-28
    Gecia Bravo-Hermsdorff; Valkyrie Felso; Emily Ray; Lee M. Gunderson; Mary E. Helander; Joana Maria; Yael Niv

    One can point to a variety of historical milestones for gender equality in STEM (science, technology, engineering, and mathematics), however, practical effects are incremental and ongoing. It is important to quantify gender differences in subdomains of scientific work in order to detect potential biases and monitor progress. In this work, we study the relevance of gender in scientific collaboration

    更新日期:2019-11-28
  • A general deep learning framework for network reconstruction and dynamics learning
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-11-26
    Zhang Zhang; Yi Zhao; Jing Liu; Shuo Wang; Ruyi Tao; Ruyue Xin; Jiang Zhang

    Many complex processes can be viewed as dynamical systems on networks. However, in real cases, only the performances of the system are known, the network structure and the dynamical rules are not observed. Therefore, recovering latent network structure and dynamics from observed time series data are important tasks because it may help us to open the black box, and even to build up the model of a complex

    更新日期:2019-11-26
  • Model-based learning of information diffusion in social media networks
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-11-26
    Zhecheng Qiang; Eduardo L. Pasiliao; Qipeng P. Zheng

    Social networks have become widely used platforms for their users to share information. Learning the information diffusion process is essential for successful applications of viral marketing and cyber security in social media networks. This paper proposes two learning models that are aimed at learning person-to-person influence in information diffusion from historical cascades based on the threshold

    更新日期:2019-11-26
  • Networks of need: a geospatial analysis of secondary cities
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-11-21
    Amanda Shores; Hanna Johnson; Debbie Fugate; Melinda Laituri

    Introduction Urbanization and the continued growth of cities, both demographically and spatially, are topics of research studied across a range of disciplines in the urban millennium — a time in history when the majority of people live in cities. However, scholarly research has focused little attention on secondary cities, despite being the most rapidly growing cities in many low-and middle-income

    更新日期:2019-11-21
  • Exact analysis of summary statistics for continuous-time discrete-state Markov processes on networks using graph-automorphism lumping
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-11-20
    Jonathan A. Ward; Martín López-García

    We propose a unified framework to represent a wide range of continuous-time discrete-state Markov processes on networks, and show how many network dynamics models in the literature can be represented in this unified framework. We show how a particular sub-set of these models, referred to here as single-vertex-transition (SVT) processes, lead to the analysis of quasi-birth-and-death (QBD) processes

    更新日期:2019-11-20
  • A family of tractable graph metrics
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-11-15
    José Bento; Stratis Ioannidis

    Important data mining problems such as nearest-neighbor search and clustering admit theoretical guarantees when restricted to objects embedded in a metric space. Graphs are ubiquitous, and clustering and classification over graphs arise in diverse areas, including, e.g., image processing and social networks. Unfortunately, popular distance scores used in these applications, that scale over large graphs

    更新日期:2019-11-15
  • Analytics for directed contact networks
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-11-15
    George Cybenko; Steve Huntsman

    Directed contact networks (DCNs) are temporal networks that are useful for analyzing and modeling phenomena in transportation, communications, epidemiology and social networking. Specific sequences of contacts can underlie higher-level behaviors such as flows that aggregate contacts based on some notion of semantic and temporal proximity. We describe a simple inhomogeneous Markov model to infer flows

    更新日期:2019-11-15
  • Toward epidemic thresholds on temporal networks: a review and open questions
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-11-14
    Jack Leitch; Kathleen A. Alexander; Srijan Sengupta

    Epidemiological contact network models have emerged as an important tool in understanding and predicting spread of infectious disease, due to their capacity to engage individual heterogeneity that may underlie essential dynamics of a particular host-pathogen system. Just as fundamental are the changes that real-world contact networks undergo over time, both independently of and in response to pathogen

    更新日期:2019-11-14
  • Anticipating employment location patterns in economic regions: modeling complex dynamics
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-11-13
    Sanda Kaufman; Miron Kaufman; Mark Salling

    Complex social-ecological systems—such as cities and regions—change in time whether or not we intervene through plans and policies. This is due in part to the numerous individual and organizational actors who make self-interested, unilateral decisions. Public decision makers are expected to act in the public interest and are accountable to constituents. They need the ability to explore alternatives

    更新日期:2019-11-13
  • Graph-based exploration and clustering analysis of semantic spaces
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-11-13
    Alexander Veremyev; Alexander Semenov; Eduardo L. Pasiliao; Vladimir Boginski

    The goal of this study is to demonstrate how network science and graph theory tools and concepts can be effectively used for exploring and comparing semantic spaces of word embeddings and lexical databases. Specifically, we construct semantic networks based on word2vec representation of words, which is “learnt” from large text corpora (Google news, Amazon reviews), and “human built” word networks derived

    更新日期:2019-11-13
  • Optimal structure of groups under exposure to fake news
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-11-08
    Evelin Berekméri; Imre Derényi; Anna Zafeiris

    Humans predominantly form their beliefs based on communication with other humans rather than direct observations, even on matters of facts, such as the shape of the globe or the effects of child vaccinations. Despite the fact that this is a well-known (not to say: trivial) observation, literature on opinion dynamics and opinion formation largely overlooks this circumstance. In the present paper we

    更新日期:2019-11-08
  • 5G device-to-device communication security and multipath routing solutions
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-11-08
    Aslihan Celik; Jessica Tetzner; Koushik Sinha; John Matta

    Through direct communication, device-to-device (D2D) technology can increase the overall throughput, enhance the coverage, and reduce the power consumption of cellular communications. Security will be of paramount importance in 5G, because 5G devices will directly affect our safety, such as by steering self-driving vehicles and controlling health care applications. 5G will be supporting millions of

    更新日期:2019-11-08
  • Compressive closeness in networks
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-11-06
    Hamidreza Mahyar; Rouzbeh Hasheminezhad; H Eugene Stanley

    Distributed algorithms for network science applications are of great importance due to today’s large real-world networks. In such algorithms, a node is allowed only to have local interactions with its immediate neighbors; because the whole network topological structure is often unknown to each node. Recently, distributed detection of central nodes, concerning different notions of importance, within

    更新日期:2019-11-06
  • Optimal shattering of complex networks
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-11-04
    Nicole Balashov; Reuven Cohen; Avieli Haber; Michael Krivelevich; Simi Haber

    We consider optimal attacks or immunization schemes on different models of random graphs. We derive bounds for the minimum number of nodes needed to be removed from a network such that all remaining components are fragments of negligible size.We obtain bounds for different regimes of random regular graphs, Erdős-Rényi random graphs, and scale free networks, some of which are tight. We show that the

    更新日期:2019-11-04
  • Towards intelligent complex networks: the space and prediction of information walks.
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-07-02
    Chuankai An,A James O'Malley,Daniel N Rockmore

    In this paper we study the problem of walk-specific information spread in directed complex social networks. Classical models usually analyze the "explosive" spread of information on social networks (e.g., Twitter) - a broadcast or epidemiological model focusing on the dynamics of a given source node "infecting" multiple targets. Less studied, but of equal importance is the case of single-track information

    更新日期:2019-11-01
  • From free text to clusters of content in health records: an unsupervised graph partitioning approach.
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2019-03-25
    M Tarik Altuncu,Erik Mayer,Sophia N Yaliraki,Mauricio Barahona

    Electronic healthcare records contain large volumes of unstructured data in different forms. Free text constitutes a large portion of such data, yet this source of richly detailed information often remains under-used in practice because of a lack of suitable methodologies to extract interpretable content in a timely manner. Here we apply network-theoretical tools to the analysis of free text in Hospital

    更新日期:2019-11-01
  • Comparison of physician networks constructed from thresholded ties versus shared clinical episodes.
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2018-01-01
    Jukka-Pekka Onnela,A James O'Malley,Nancy L Keating,Bruce E Landon

    Objective To compare standard methods for constructing physician networks from patient-physician encounter data with a new method based on clinical episodes of care. Data source We used data on 100% of traditional Medicare beneficiaries from 51 nationally representative geographical regions for the years 2005-2010. Study design We constructed networks of physicians based on their shared patients. In

    更新日期:2019-11-01
  • Referral paths in the U.S. physician network.
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2018-01-01
    Chuankai An,A James O'Malley,Daniel N Rockmore

    In this paper, we analyze the millions of referral paths of patients' interactions with the healthcare system for each year in the 2006-2011 time period and relate them to U.S. cardiovascular treatment records. For a patient, a "referral path" records the chronological sequence of physicians encountered by a patient (subject to certain constraints on the times between encounters). It provides a basic

    更新日期:2019-11-01
  • δ-MAPS: from spatio-temporal data to a weighted and lagged network between functional domains.
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2018-01-01
    Ilias Fountalis,Constantine Dovrolis,Annalisa Bracco,Bistra Dilkina,Shella Keilholz

    In real physical systems the underlying spatial components might not have crisp boundaries and their interactions might not be instantaneous. To this end, we propose δ-MAPS; a method that identifies spatially contiguous and possibly overlapping components referred to as domains, and identifies the lagged functional relationships between them. Informally, a domain is a spatially contiguous region that

    更新日期:2019-11-01
  • Evolution of threats in the global risk network.
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2018-01-01
    Xiang Niu,Alaa Moussawi,Gyorgy Korniss,Boleslaw K Szymanski

    With a steadily growing population and rapid advancements in technology, the global economy is increasing in size and complexity. This growth exacerbates global vulnerabilities and may lead to unforeseen consequences such as global pandemics fueled by air travel, cyberspace attacks, and cascading failures caused by the weakest link in a supply chain. Hence, a quantitative understanding of the mechanisms

    更新日期:2019-11-01
  • The orthographic similarity structure of English words: Insights from network science.
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2018-01-01
    Cynthia S Q Siew

    Network science has been applied to study the structure of the mental lexicon, the part of long-term memory where all the words a person knows are stored. Here the tools of network science are used to study the organization of orthographic word-forms in the mental lexicon and how that might influence visual word recognition. An orthographic similarity network of the English language was constructed

    更新日期:2019-11-01
  • Replicator equation on networks with degree regular communities.
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2018-01-01
    Daniele Cassese

    The replicator equation is one of the fundamental tools to study evolutionary dynamics in well-mixed populations. This paper contributes to the literature on evolutionary graph theory, providing a version of the replicator equation for a family of connected networks with communities, where nodes in the same community have the same degree. This replicator equation is applied to the study of different

    更新日期:2019-11-01
  • Designing bike networks using the concept of network clusters.
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2018-01-01
    Meisam Akbarzadeh,Syed Sina Mohri,Ehsan Yazdian

    In this paper, a novel method is proposed for designing a bike network in urban areas. Based on the number of taxi trips within an urban area, a weighted network is abstracted. In this network, nodes are the origins and destinations of taxi trips and the number of trips among them is abstracted as link weights. Data is extracted from the Taxi smart card system of a real city. Then, Communities i.e

    更新日期:2019-11-01
  • The gravity of an edge.
    Appl. Netw. Sci. (IF 0.0) Pub Date : 2018-01-01
    Mary E Helander,Sarah McAllister

    We describe a methodology for characterizing the relative structural importance of an arbitrary network edge by exploiting the properties of a k-shortest path algorithm. We introduce the metric Edge Gravity, measuring how often an edge occurs in any possible network path, as well as k-Gravity, a lower bound based on paths enumerated while solving the k-shortest path problem. The methodology is demonstrated

    更新日期:2019-11-01
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