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  • Gender-specific behavior change following terror attacks
    arXiv.cs.SI Pub Date : 2020-04-06
    Jonas S. Juul; Laura Alessandretti; Jesper Dammeyer; Ingo Zettler; Sune Lehmann; Joachim Mathiesen

    Terrorists use violence in pursuit of political goals. While terror often has severe consequences for victims, it remains an open question how terror attacks affect the general population. We study the behavioral response of citizens of cities affected by $7$ different terror attacks. We compare real-time mobile communication patterns in the first $24$ hours following a terror attack to the corresponding

    更新日期:2020-04-08
  • On the Persistence of Persistent Identifiers of the Scholarly Web
    arXiv.cs.SI Pub Date : 2020-04-06
    Martin Klein; Lyudmila Balakireva

    Scholarly resources, just like any other resources on the web, are subject to reference rot as they frequently disappear or significantly change over time. Digital Object Identifiers (DOIs) are commonplace to persistently identify scholarly resources and have become the de facto standard for citing them. We investigate the notion of persistence of DOIs by analyzing their resolution on the web. We derive

    更新日期:2020-04-08
  • Graph Distances and Clustering
    arXiv.cs.SI Pub Date : 2020-04-06
    Pierre Miasnikof; Alexander Y. Shestopaloff; Leonidas Pitsoulis; Yuri Lawryshyn

    With a view on graph clustering, we present a definition of vertex-to-vertex distance which is based on shared connectivity. We argue that vertices sharing more connections are closer to each other than vertices sharing fewer connections. Our thesis is centered on the widely accepted notion that strong clusters are formed by high levels of induced subgraph density, where subgraphs represent clusters

    更新日期:2020-04-08
  • The geographic spread of COVID-19 correlates with structure of social networks as measured by Facebook
    arXiv.cs.SI Pub Date : 2020-04-07
    Theresa Kuchler; Dominic Russel; Johannes Stroebel

    We use anonymized and aggregated data from Facebook to show that areas with stronger social ties to two early COVID-19 "hotspots" (Westchester County, NY, in the U.S. and Lodi province in Italy) generally have more confirmed COVID-19 cases as of March 30, 2020. These relationships hold after controlling for geographic distance to the hotspots as well as for the income and population density of the

    更新日期:2020-04-08
  • Statistical properties of telephone communication network
    arXiv.cs.SI Pub Date : 2020-04-07
    V. M. Danilevskiy; V. V. Yanovsky

    The directed network of telephone subscribers is considered in the article. It can be described as a dynamic network with vertices that correspond to the subscribers of the telephone network and emerging directional edges that correspond to the connections between the respective subscribers. The position of the edge and its direction is determined by the incoming and outgoing calls from the corresponding

    更新日期:2020-04-08
  • Discovering associations in COVID-19 related research papers
    arXiv.cs.SI Pub Date : 2020-04-06
    Iztok Fister Jr.; Karin Fister; Iztok Fister

    A COVID-19 pandemic has already proven itself to be a global challenge. It proves how vulnerable humanity can be. It has also mobilized researchers from different sciences and different countries in the search for a way to fight this potentially fatal disease. In line with this, our study analyses the abstracts of papers related to COVID-19 and coronavirus-related-research using association rule text

    更新日期:2020-04-08
  • General Community Detection with Optimal Recovery Conditions for Multi-relational Sparse Networks with Dependent Layers
    arXiv.cs.SI Pub Date : 2020-04-06
    Sharmodeep Bhattacharyya; Shirshendu Chatterjee

    Multilayer and multiplex networks are becoming common network data sets in recent times. We consider the problem of identifying the common community structure for a special type of multilayer networks called multi-relational networks. We consider extensions of the spectral clustering methods for multi-relational networks and give theoretical guarantees that the spectral clustering methods recover community

    更新日期:2020-04-08
  • Routine pattern discovery and anomaly detection in individual travel behavior
    arXiv.cs.SI Pub Date : 2020-04-05
    Lijun Sun; Xinyu Chen; Zhaocheng He; Luis F. Miranda-Moreno

    Discovering patterns and detecting anomalies in individual travel behavior is a crucial problem in both research and practice. In this paper, we address this problem by building a probabilistic framework to model individual spatiotemporal travel behavior data (e.g., trip records and trajectory data). We develop a two-dimensional latent Dirichlet allocation (LDA) model to characterize the generative

    更新日期:2020-04-08
  • A Few Topical Tweets are Enough for Effective User-Level Stance Detection
    arXiv.cs.SI Pub Date : 2020-04-07
    Younes Samih; Kareem Darwish

    Stance detection entails ascertaining the position of a user towards a target, such as an entity, topic, or claim. Recent work that employs unsupervised classification has shown that performing stance detection on vocal Twitter users, who have many tweets on a target, can yield very high accuracy (+98%). However, such methods perform poorly or fail completely for less vocal users, who may have authored

    更新日期:2020-04-08
  • Divergent modes of online collective attention to the COVID-19 pandemic are associated with future caseload variance
    arXiv.cs.SI Pub Date : 2020-04-07
    David Rushing Dewhurst; Thayer Alshaabi; Michael V. Arnold; Joshua R. Minot; Christopher M. Danforth; Peter Sheridan Dodds

    Using a random 10% sample of tweets authored from 2019-09-01 through 2020-03-25, we analyze the dynamic behavior of words (1-grams) used on Twitter to describe the ongoing COVID-19 pandemic. Across 24 languages, we find two distinct dynamic regimes: One characterizing the rise and subsequent collapse in collective attention to the initial Coronavirus outbreak in late January, and a second that represents

    更新日期:2020-04-08
  • Normalised Degree Variance
    arXiv.cs.SI Pub Date : 2018-03-08
    Keith M. Smith; Javier Escudero

    Finding graph indices which are unbiased to network size and density is of high importance both within a given field and across fields for enhancing comparability of modern network science studies. The degree variance is an important metric for characterising network degree heterogeneity. Here, we provide an analytically valid normalisation of degree variance to replace previous normalisations which

    更新日期:2020-04-08
  • Policy Targeting under Network Interference
    arXiv.cs.SI Pub Date : 2019-06-24
    Davide Viviano

    This paper discusses the problem of estimating treatment allocation rules under network interference. I propose a method with several attractive features for applications: (i) it does not rely on the correct specification of a particular structural model; (ii) it exploits heterogeneity in treatment effects for targeting individuals; (iii) it accommodates arbitrary constraints on the policy function

    更新日期:2020-04-08
  • Pandemic Populism: Facebook Pages of Alternative News Media and the Corona Crisis -- A Computational Content Analysis
    arXiv.cs.SI Pub Date : 2020-04-06
    Svenja Boberg; Thorsten Quandt; Tim Schatto-Eckrodt; Lena Frischlich

    The COVID-19 pandemic has not only had severe political, economic, and societal effects, it has also affected media and communication systems in unprecedented ways. While traditional journalistic media has tried to adapt to the rapidly evolving situation, alternative news media on the Internet have given the events their own ideological spin. Such voices have been criticized for furthering societal

    更新日期:2020-04-08
  • Robustness analysis in an inter-cities mobility network: modeling municipal, state and federal initiatives as failures and attacks
    arXiv.cs.SI Pub Date : 2020-04-06
    Vander L. S. Freitas; Jeferson Feitosa; Catia S. N. Sepetauskas; Leonardo B. L. Santos

    Motivated by the challenge related to the COVID-19 epidemic and the seek for optimal containment strategies, we present a robustness analysis into an inter-cities mobility complex network. We abstract municipal initiatives as nodes' failures and the federal actions as targeted attacks. The geo(graphs) approach is applied to visualize the geographical graph and produce maps of topological indexes, such

    更新日期:2020-04-08
  • Motif-Based Spectral Clustering of Weighted Directed Networks
    arXiv.cs.SI Pub Date : 2020-04-02
    William George Underwood; Andrew Elliott; Mihai Cucuringu

    Clustering is an essential technique for network analysis, with applications in a diverse range of fields. Although spectral clustering is a popular and effective method, it fails to consider higher-order structure and can perform poorly on directed networks. One approach is to capture and cluster higher-order structures using motif adjacency matrices. However, current formulations fail to take edge

    更新日期:2020-04-06
  • From Paris to Berlin: Discovering Fashion Style Influences Around the World
    arXiv.cs.SI Pub Date : 2020-04-03
    Ziad Al-Halah; Kristen Grauman

    The evolution of clothing styles and their migration across the world is intriguing, yet difficult to describe quantitatively. We propose to discover and quantify fashion influences from everyday images of people wearing clothes. We introduce an approach that detects which cities influence which other cities in terms of propagating their styles. We then leverage the discovered influence patterns to

    更新日期:2020-04-06
  • How mobility patterns drive disease spread: A case study using public transit passenger card travel data
    arXiv.cs.SI Pub Date : 2020-04-03
    Ahmad El ShoghriSchool of Computer Science and Engineering, University of New South Wales, Sydney, AUSTRALIAData61, Commonwealth Scientific and Industrial Research Organization, Brisbane, AUSTRALIA; Jessica LiebigData61, Commonwealth Scientific and Industrial Research Organization, Brisbane, AUSTRALIA; Lauren GardnerSchool of Civil and Environmental Engineering, University of New South Wales, Sydney

    Outbreaks of infectious diseases present a global threat to human health and are considered a major health-care challenge. One major driver for the rapid spatial spread of diseases is human mobility. In particular, the travel patterns of individuals determine their spreading potential to a great extent. These travel behaviors can be captured and modelled using novel location-based data sources, e.g

    更新日期:2020-04-06
  • Bridging the gap between graphs and networks
    arXiv.cs.SI Pub Date : 2020-04-03
    Gerardo Iñiguez; Federico Battiston; Márton Karsai

    Network science has become a powerful tool to describe the structure and dynamics of real-world complex physical, biological, social, and technological systems. Largely built on empirical observations to tackle heterogeneous, temporal, and adaptive patterns of interactions, its intuitive and flexible nature has contributed to the popularity of the field. With pioneering work on the evolution of random

    更新日期:2020-04-06
  • Localized Mobile Agent Framework for data processing on Internet of Things
    arXiv.cs.SI Pub Date : 2020-04-03
    J. Mahalakshmi; P. Venkata Krishna

    Internet of Things (IoT) is the major research filed in the recent trends. IoT has the ability to create communication with any object. IoT produces big amount of raw data at the time of data gathering. Therefore, there is a need of efficient mechanism to address the issue of IoT. This paper presents the localized MapReduce Framework for IoT. This frame work processes the data at the local nodes without

    更新日期:2020-04-06
  • Layer entanglement in multiplex, temporal multiplex, and coupled multilayer networks
    arXiv.cs.SI Pub Date : 2020-04-02
    Blaž Škrlj; Benjamin Renoust

    Complex networks, such as transportation networks, social networks, or biological networks, translate the complex system they model often by representing one type of interactions. In real world systems, there may be many aspects of the entities that connects them together. These can be captured using multilayer networks, which combine different modalities of interactions in one same model. Coupling

    更新日期:2020-04-06
  • Identifying highly influential travellers for spreading disease on a public transport system
    arXiv.cs.SI Pub Date : 2020-04-03
    Ahmad El ShoghriSchool of Computer Science and Engineering, University of New South Wales, Sydney, AustraliaData61, Commonwealth Scientific and Industrial Research Organization, Brisbane, Australia; Jessica LiebigData61, Commonwealth Scientific and Industrial Research Organization, Brisbane, Australia; Raja JurdakData61, Commonwealth Scientific and Industrial Research Organization, Brisbane, AustraliaSchool

    The recent outbreak of a novel coronavirus and its rapid spread underlines the importance of understanding human mobility. Enclosed spaces, such as public transport vehicles (e.g. buses and trains), offer a suitable environment for infections to spread widely and quickly. Investigating the movement patterns and the physical encounters of individuals on public transit systems is thus critical to understand

    更新日期:2020-04-06
  • Comparing spatial networks: A 'one size fits all' efficiency-driven approach
    arXiv.cs.SI Pub Date : 2018-07-02
    Ignacio Morer; Alessio Cardillo; Albert Diaz-Guilera; Luce Prignano; Sergi Lozano

    Spatial networks are a powerful framework for studying a large variety of systems belonging to a broad diversity of contexts: from transportation to biology, from epidemiology to communications, and migrations, to cite a few. Spatial networks can be described in terms of their total cost (i.e. the total amount of resources needed for building or traveling their connections). Here, we address the issue

    更新日期:2020-04-06
  • The Wigner's Semicircle Law of Weighted Random Networks
    arXiv.cs.SI Pub Date : 2020-03-31
    Yusuke Sakumoto; Masaki Aida

    The spectral graph theory provides an algebraical approach to investigate the characteristics of weighted networks using the eigenvalues and eigenvectors of a matrix (e.g., normalized Laplacian matrix) that represents the structure of the network. However, it is difficult for large-scale and complex networks (e.g., social network) to represent their structure as a matrix correctly. If there is a universality

    更新日期:2020-04-06
  • Time-aware Gradient Attack on Dynamic Network Link Prediction
    arXiv.cs.SI Pub Date : 2019-11-24
    Jinyin Chen; Jian Zhang; Zhi Chen; Min Du; Qi Xuan

    In network link prediction, it is possible to hide a target link from being predicted with a small perturbation on network structure. This observation may be exploited in many real world scenarios, for example, to preserve privacy, or to exploit financial security. There have been many recent studies to generate adversarial examples to mislead deep learning models on graph data. However, none of the

    更新日期:2020-04-06
  • A k-hop Collaborate Game Model: Extended to Community Budgets and Adaptive Non-Submodularity
    arXiv.cs.SI Pub Date : 2020-04-02
    Jianxiong Guo; Weili Wu

    Revenue maximization (RM) is one of the most important problems on online social networks (OSNs), which attempts to find a small subset of users in OSNs that makes the expected revenue maximized. It has been researched intensively before. However, most of exsiting literatures were based on non-adaptive seeding strategy and on simple information diffusion model, such as IC/LT-model. It considered the

    更新日期:2020-04-03
  • #ArsonEmergency and Australia's "Black Summer": Polarisation and misinformation on social media
    arXiv.cs.SI Pub Date : 2020-04-01
    Derek Weber; Mehwish Nasim; Lucia Falzon; Lewis Mitchell

    During the summer of 2019-20, while Australia suffered unprecedented bushfires across the country, false narratives regarding arson and limited backburning spread quickly on Twitter, particularly using the hashtag #ArsonEmergency. Misinformation and bot- and troll-like behaviour were detected and reported by social media researchers and the news soon reached mainstream media. This paper examines the

    更新日期:2020-04-03
  • Spotting political social bots in Twitter: A use case of the 2019 Spanish general election
    arXiv.cs.SI Pub Date : 2020-04-02
    Javier Pastor-Galindo; Mattia Zago; Pantaleone Nespoli; Sergio López Bernal; Alberto Huertas Celdrán; Manuel Gil Pérez; José A. Ruipérez-Valiente; Gregorio Martínez Pérez; Félix Gómez Mármol

    While social media has been proved as an exceptionally useful tool to interact with other people and massively and quickly spread helpful information, its great potential has been ill-intentionally leveraged as well to distort political elections and manipulate constituents. In the paper at hand, we analyzed the presence and behavior of social bots on Twitter in the context of the November 2019 Spanish

    更新日期:2020-04-03
  • Modeling Dynamic Heterogeneous Network for Link Prediction using Hierarchical Attention with Temporal RNN
    arXiv.cs.SI Pub Date : 2020-04-01
    Hansheng Xue; Luwei Yang; Wen Jiang; Yi Wei; Yi Hu; Yu Lin

    Network embedding aims to learn low-dimensional representations of nodes while capturing structure information of networks. It has achieved great success on many tasks of network analysis such as link prediction and node classification. Most of existing network embedding algorithms focus on how to learn static homogeneous networks effectively. However, networks in the real world are more complex, e

    更新日期:2020-04-03
  • Generate Country-Scale Networks of Interaction from Scattered Statistics
    arXiv.cs.SI Pub Date : 2020-04-01
    Samuel Thiriot; Jean-Daniel Kant

    It is common to define the structure of interactions among a population of agents by a network. Most of agent-based models were shown highly sensitive to that network, so the relevance of simulation results directely depends on the descriptive power of that network. When studying social dynamics in large populations, that network cannot be collected, and is rather generated by algorithms which aim

    更新日期:2020-04-03
  • The Paradox of Information Access: On Modeling Social-Media-Induced Polarization
    arXiv.cs.SI Pub Date : 2020-04-02
    Chao Xu; Jinyang Li; Tarek Abdelzaher; Heng Ji; Boleslaw K. Szymanski; John Dellaverson

    The paper develops a stochastic model of drift in human beliefs that shows that today's sheer volume of accessible information, combined with consumers' confirmation bias and natural preference to more outlying content, necessarily lead to increased polarization. The model explains the paradox of growing ideological fragmentation in the age of increased sharing. As social media, search engines, and

    更新日期:2020-04-03
  • Stopping explosion by penalising transmission to hubs in scale-free spatial random graphs
    arXiv.cs.SI Pub Date : 2020-04-02
    Júlia Komjáthy; John Lapinskas; Johannes Lengler

    We study the spread of information in finite and infinite inhomogeneous spatial random graphs. We assume that each edge has a transmission cost that is a product of an i.i.d. random variable L and a penalty factor: edges between vertices of expected degrees w_1 and w_2 are penalised by a factor of (w_1w_2)^\mu for all \mu >0. We study this process for scale-free percolation, for (finite and infinite)

    更新日期:2020-04-03
  • Homophily as a Process Generating Social Networks: Insights from Social Distance Attachment Model
    arXiv.cs.SI Pub Date : 2019-07-16
    Szymon Talaga; Andrzej Nowak

    Real-world social networks often exhibit high levels of clustering, positive degree assortativity, short average path lengths (small-world property) and right-skewed but rarely power law degree distributions. On the other hand homophily, defined as the propensity of similar agents to connect to each other, is one of the most fundamental social processes observed in many human and animal societies.

    更新日期:2020-04-03
  • Caching as an Image Characterization Problem using Deep Convolutional Neural Networks
    arXiv.cs.SI Pub Date : 2019-07-16
    Yantong Wang; Vasilis Friderikos

    Caching of popular content closer to the mobile user can significantly increase overall user experience as well as network efficiency by decongesting backbone network segments in the case of congestion episodes. In order to find the optimal caching locations, many conventional approaches rely on solving a complex optimization problem that suffers from the curse of dimensionality, which may fail to

    更新日期:2020-04-03
  • A Survey on Computational Politics
    arXiv.cs.SI Pub Date : 2019-08-16
    Ehsan ul Haq; Tristan Braud; Young D. Kwon; Pan Hui

    Computational Politics is the study of computational methods to analyze and moderate users' behaviors related to political activities such as election campaign persuasion, political affiliation, and opinion mining. With the rapid development and ease of access to the Internet, Information Communication Technologies (ICT) have given rise to massive numbers of users joining online communities and the

    更新日期:2020-04-03
  • Analysing the Extent of Misinformation in Cancer Related Tweets
    arXiv.cs.SI Pub Date : 2020-03-30
    Rakesh Bal; Sayan Sinha; Swastika Dutta; Rishabh Joshi; Sayan Ghosh; Ritam Dutt

    Twitter has become one of the most sought after places to discuss a wide variety of topics, including medically relevant issues such as cancer. This helps spread awareness regarding the various causes, cures and prevention methods of cancer. However, no proper analysis has been performed, which discusses the validity of such claims. In this work, we aim to tackle the misinformation spread in such platforms

    更新日期:2020-04-03
  • Coronavirus Covid-19 spreading in Italy: optimizing an epidemiological model with dynamic social distancing through Differential Evolution
    arXiv.cs.SI Pub Date : 2020-04-01
    I. De Falco; A. Della Cioppa; U. Scafuri; E. Tarantino

    The aim of this paper consists in the application of a recent epidemiological model, namely SEIR with Social Distancing (SEIR--SD), extended here through the definition of a social distancing function varying over time, to assess the situation related to the spreading of the coronavirus Covid--19 in Italy and in two of its most important regions, i.e., Lombardy and Campania. To profitably use this

    更新日期:2020-04-03
  • Graph Summarization Methods and Applications: A Survey
    arXiv.cs.SI Pub Date : 2016-12-14
    Yike Liu; Tara Safavi; Abhilash Dighe; Danai Koutra

    While advances in computing resources have made processing enormous amounts of data possible, human ability to identify patterns in such data has not scaled accordingly. Efficient computational methods for condensing and simplifying data are thus becoming vital for extracting actionable insights. In particular, while data summarization techniques have been studied extensively, only recently has summarizing

    更新日期:2020-04-03
  • Social-Sensor Composition for Tapestry Scenes
    arXiv.cs.SI Pub Date : 2020-03-28
    Tooba Aamir; Hai Dong; Athman Bouguettaya

    The extensive use of social media platforms and overwhelming amounts of imagery data creates unique opportunities for sensing, gathering and sharing information about events. One of its potential applications is to leverage crowdsourced social media images to create a tapestry scene for scene analysis of designated locations and time intervals. The existing attempts however ignore the temporal-semantic

    更新日期:2020-04-01
  • Quantum Godwin's Law
    arXiv.cs.SI Pub Date : 2020-03-30
    Michalis Skotiniotis; Andreas Winter

    Godwin's law, i.e. the empirical observation that as an online discussion grows in time, the probability of a comparison with Nazis or Hitler quickly approaches unity, is one of the best-documented facts of the internet. Anticipating the quantum internet, here we show under reasonable model assumptions a polynomial quantum speedup of Godwin's law. Concretely, in quantum discussions, Hitler will be

    更新日期:2020-04-01
  • Quasi-experimental Designs for Assessing Response on Social Media to Policy Changes
    arXiv.cs.SI Pub Date : 2020-03-30
    Yijun Tian; Rumi Chunara

    Regulation of tobacco products is rapidly evolving. Understanding public sentiment in response to changes is very important as authorities assess how to effectively protect population health. Social media systems are widely recognized to be useful for collecting data about human preferences and perceptions. However, how social media data may be used, in rapid policy change settings, given challenges

    更新日期:2020-04-01
  • Social Media Mining Toolkit (SMMT)
    arXiv.cs.SI Pub Date : 2020-03-31
    Ramya Tekumalla; Juan M. Banda

    There has been a dramatic increase in the popularity of utilizing social media data for research purposes within the biomedical community. In PubMed alone, there have been nearly 2,500 publication entries since 2014 that deal with analyzing social media data from Twitter and Reddit. However, the vast majority of those works do not share their code or data for replicating their studies. With minimal

    更新日期:2020-04-01
  • A large-scale Twitter dataset for drug safety applications mined from publicly existing resources
    arXiv.cs.SI Pub Date : 2020-03-31
    Ramya Tekumalla; Juan M. Banda

    With the increase in popularity of deep learning models for natural language processing (NLP) tasks, in the field of Pharmacovigilance, more specifically for the identification of Adverse Drug Reactions (ADRs), there is an inherent need for large-scale social-media datasets aimed at such tasks. With most researchers allocating large amounts of time to crawl Twitter or buying expensive pre-curated datasets

    更新日期:2020-04-01
  • A first look at COVID-19 information and misinformation sharing on Twitter
    arXiv.cs.SI Pub Date : 2020-03-31
    Lisa Singh; Shweta Bansal; Leticia Bode; Ceren Budak; Guangqing Chi; Kornraphop Kawintiranon; Colton Padden; Rebecca Vanarsdall; Emily Vraga; Yanchen Wang

    Since December 2019, COVID-19 has been spreading rapidly across the world. Not surprisingly, conversation about COVID-19 is also increasing. This article is a first look at the amount of conversation taking place on social media, specifically Twitter, with respect to COVID-19, the themes of discussion, where the discussion is emerging from, myths shared about the virus, and how much of it is connected

    更新日期:2020-04-01
  • A Robust Gradient Tracking Method for Distributed Optimization over Directed Networks
    arXiv.cs.SI Pub Date : 2020-03-31
    Shi Pu

    In this paper, we consider the problem of distributed consensus optimization over multi-agent networks with directed network topology. Assuming each agent has a local cost function that is smooth and strongly convex, the global objective is to minimize the average of all the local cost functions. To solve the problem, we introduce a robust gradient tracking method (R-Push-Pull) adapted from the recently

    更新日期:2020-04-01
  • The propagation of the economic impact through supply chains: The case of a mega-city lockdown against the spread of COVID-19
    arXiv.cs.SI Pub Date : 2020-03-31
    Hiroyasu Inoue; Yasuyuki Todo

    This study quantifies the economic effect of a possible lockdown of Tokyo to prevent spread of COVID-19. The negative effect of the lockdown may propagate to other regions through supply chains because of shortage of supply and demand. Applying an agent-based model to the actual supply chains of nearly 1.6 million firms in Japan, we simulate what would happen to production activities outside Tokyo

    更新日期:2020-04-01
  • Problems with classification, hypothesis testing, and estimator convergence in the analysis of degree distributions in networks
    arXiv.cs.SI Pub Date : 2020-03-31
    Pim van der Hoorn; Ivan Voitalov; Remco van der Hofstad; Dmitri Krioukov

    In their recent work "Scale-free networks are rare", Broido and Clauset address the problem of the analysis of degree distributions in networks to classify them as scale-free at different strengths of "scale-freeness." Over the last two decades, a multitude of papers in network science have reported that the degree distributions in many real-world networks follow power laws. Such networks were then

    更新日期:2020-04-01
  • Understanding the COVID19 Outbreak: A Comparative Data Analytics and Study
    arXiv.cs.SI Pub Date : 2020-03-29
    Anis Koubaa

    The Coronavirus, also known as the COVID-19 virus, has emerged in Wuhan China since late November 2019. Since that time, it has been spreading at large-scale until today all around the world. It is currently recognized as the world's most viral and severe epidemic spread in the last twenty years, as compared to Ebola 2014, MERS 2012, and SARS 2003. Despite being still in the middle of the outbreak

    更新日期:2020-04-01
  • Mobility Changes in Response to COVID-19
    arXiv.cs.SI Pub Date : 2020-03-31
    Michael S. Warren; Samuel W. Skillman

    In response to the COVID-19 pandemic, both voluntary changes in behavior and administrative restrictions on human interactions have occurred. These actions are intended to reduce the transmission rate of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We use anonymized and/or de-identified mobile device locations to measure mobility, a statistic representing the distance a typical

    更新日期:2020-04-01
  • A Fully Distributed, Privacy Respecting Approach for Back-tracking of Potentially Infectious Contacts
    arXiv.cs.SI Pub Date : 2020-03-31
    Adam Wolisz

    In limiting the rapid spread of highly infectious diseases like Covid-19 means to immediately identify individuals who had been in contact with a newly diagnosed infected person have proven to be important. Such potential victims can go into quarantine until tested thus constraining further spread. This note describes a concept of mobile device (e.g. Smart phones) based approach for tracking interpersonal

    更新日期:2020-04-01
  • Hurricanes and hashtags: Characterizing online collective attention for natural disasters
    arXiv.cs.SI Pub Date : 2020-03-31
    Michael V. Arnold; David Rushing Dewhurst; Thayer Alshaabi; Joshua R. Minot; Jane L. Adams; Christopher M. Danforth; Peter Sheridan Dodds

    We study collective attention paid towards hurricanes through the lens of $n$-grams on Twitter, a social media platform with global reach. Using hurricane name mentions as a proxy for awareness, we find that the exogenous temporal dynamics are remarkably similar across storms, but that overall collective attention varies widely even among storms causing comparable deaths and damage. We construct `hurricane

    更新日期:2020-04-01
  • A Modified SIR Model for the COVID-19 Contagion in Italy
    arXiv.cs.SI Pub Date : 2020-03-31
    Giuseppe C. Calafiore; Carlo Novara; Corrado Possieri

    The purpose of this work is to give a contribution to the understanding of the COVID-19 contagion in Italy. To this end, we developed a modified Susceptible-Infected-Recovered (SIR) model for the contagion, and we used official data of the pandemic up to March 30th, 2020 for identifying the parameters of this model. The non standard part of our approach resides in the fact that we considered as model

    更新日期:2020-04-01
  • Community Detection in Partially Observable Social Networks
    arXiv.cs.SI Pub Date : 2017-12-30
    Cong Tran; Won-Yong Shin; Andreas Spitz

    The discovery of community structures in social networks has gained significant attention since it is a fundamental problem in understanding the networks' topology and functions. However, most social network data are collected from partially observable networks with both missing nodes and edges. In this paper, we address a new problem of detecting overlapping community structures in the context of

    更新日期:2020-04-01
  • Avatar Work: Telework for Disabled People Unable to Go Outside by Using Avatar Robots "OriHime-D" and Its Verification
    arXiv.cs.SI Pub Date : 2020-03-25
    Kazuaki Takeuchi; Yoichi Yamazaki; Kentaro Yoshifuji

    In this study, we propose a telework "avatar work" that enables people with disabilities to engage in physical works such as customer service in order to realize an inclusive society, where we can do anything if we have free mind, even though we are bedridden. In avatar work, disabled people can remotely engage in physical work by operating a proposed robot "OriHime-D" with a mouse or gaze input depending

    更新日期:2020-03-31
  • How the world's collective attention is being paid to a pandemic: COVID-19 related 1-gram time series for 24 languages on Twitter
    arXiv.cs.SI Pub Date : 2020-03-27
    T. Alshaabi; J. R. Minot; M. V. Arnold; J. L. Adams; D. R. Dewhurst; A. J. Reagan; R. Muhamad; C. M. Danforth; P. S. Dodds

    In confronting the global spread of the coronavirus disease COVID-19 pandemic we must have coordinated medical, operational, and political responses. In all efforts, data is crucial. Fundamentally, and in the possible absence of a vaccine for 12 to 18 months, we need universal, well-documented testing for both the presence of the disease as well as confirmed recovery through serological tests for antibodies

    更新日期:2020-03-31
  • The impossibility of low rank representations for triangle-rich complex networks
    arXiv.cs.SI Pub Date : 2020-03-27
    C. Seshadhri; Aneesh Sharma; Andrew Stolman; Ashish Goel

    The study of complex networks is a significant development in modern science, and has enriched the social sciences, biology, physics, and computer science. Models and algorithms for such networks are pervasive in our society, and impact human behavior via social networks, search engines, and recommender systems to name a few. A widely used algorithmic technique for modeling such complex networks is

    更新日期:2020-03-31
  • Topology and Content Co-Alignment Graph Convolutional Learning
    arXiv.cs.SI Pub Date : 2020-03-28
    Min Shi; Yufei Tang; Xingquan Zhu

    In traditional Graph Neural Networks (GNN), graph convolutional learning is carried out through topology-driven recursive node content aggregation for network representation learning. In reality, network topology and node content are not always consistent because of irrelevant or missing links between nodes. A pure topology-driven feature aggregation approach between unaligned neighborhoods deteriorates

    更新日期:2020-03-31
  • Controllability of Network Opinion in Erdos-Renyi Graphs using Sparse Control Inputs
    arXiv.cs.SI Pub Date : 2020-03-28
    Geethu Joseph; Buddhika Nettasinghe; Vikram Krishnamurthy; Pramod Varshney

    This paper considers a social network modeled as an Erdos Renyi random graph. Each individual in the network updates her opinion using the weighted average of the opinions of her neighbors. We explore how an external manipulative agent can drive the opinions of these individuals to a desired state with a limited additive influence on their innate opinions. We show that the manipulative agent can steer

    更新日期:2020-03-31
  • Clickbait Detection using Multiple Categorization Techniques
    arXiv.cs.SI Pub Date : 2020-03-29
    Abinash Pujahari; Dilip Singh Sisodia

    Clickbaits are online articles with deliberately designed misleading titles for luring more and more readers to open the intended web page. Clickbaits are used to tempted visitors to click on a particular link either to monetize the landing page or to spread the false news for sensationalization. The presence of clickbaits on any news aggregator portal may lead to unpleasant experience to readers.

    更新日期:2020-03-31
  • A bibliometric analysis of research based on the Roy Adaptation Model: a contribution to Nursing
    arXiv.cs.SI Pub Date : 2020-03-29
    Paulina Hurtado-Arenas; Miguel R. Guevara

    Objective. To perform a modern bibliometric analysis of the research based on the Roy Adaptation Model, a founding nursing model proposed by Sor Callista Roy in the1970s. Method. A descriptive and longitudinal study. We used information from the two dominant scientific databases, Web Of Science and SCOPUS. We obtained 137 publications from the Core Collection of WoS, and 338 publications from SCOPUS

    更新日期:2020-03-31
  • Graphical Games and Decomposition
    arXiv.cs.SI Pub Date : 2020-03-29
    Laura Arditti; Giacomo Como; Fabio Fagnani

    We consider graphical games as introduced by Kearns et al. (2001). First we analyse the interaction of graphicality with a notion of strategic equivalence of games, providing a minimal complexity graphical description for games. Then we study the interplay between graphicality and the classical decomposition of games proposed by Candogan et al. (2011), characterizing the graphical properties of each

    更新日期:2020-03-31
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