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  • A multi-layer approach to disinformation detection in US and Italian news spreading on Twitter
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-11-23
    Francesco Pierri, Carlo Piccardi, Stefano Ceri

    We tackle the problem of classifying news articles pertaining to disinformation vs mainstream news by solely inspecting their diffusion mechanisms on Twitter. This approach is inherently simple compared to existing text-based approaches, as it allows to by-pass the multiple levels of complexity which are found in news content (e.g. grammar, syntax, style). As we employ a multi-layer representation

  • Scholarly migration within Mexico: analyzing internal migration among researchers using Scopus longitudinal bibliometric data
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-11-05
    Andrea Miranda-González, Samin Aref, Tom Theile, Emilio Zagheni

    The migration of scholars is a major driver of innovation and of diffusion of knowledge. Although large-scale bibliometric data have been used to measure international migration of scholars, our understanding of internal migration among researchers is very limited. This is partly due to a lack of data aggregated at a suitable sub-national level. In this study, we analyze internal migration in Mexico

  • A network theory of inter-firm labor flows
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-11-02
    Eduardo López, Omar A. Guerrero, Robert L. Axtell

    Using detailed administrative microdata for two countries, we build a modeling framework that yields new explanations for the origin of firm sizes, the firm contributions to unemployment, and the job-to-job mobility of workers between firms. Firms are organized as nodes in networks where connections represent low mobility barriers for workers. These labor flow networks are determined empirically, and

  • The great divide: drivers of polarization in the US public
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-10-28
    Lucas Böttcher, Hans Gersbach

    Many democratic societies have become more politically polarized, with the U.S. being the main example. The origins of this phenomenon are still not well-understood and subject to debate. To provide insight into some of the mechanisms underlying political polarization, we develop a mathematical framework and employ Bayesian Markov chain Monte-Carlo (MCMC) and information-theoretic concepts to analyze

  • Human biases in body measurement estimation
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-10-27
    Kirill Martynov, Kiran Garimella, Robert West

    Body measurements, including weight and height, are key indicators of health. Being able to visually assess body measurements reliably is a step towards increased awareness of overweight and obesity and is thus important for public health. Nevertheless it is currently not well understood how accurately humans can assess weight and height from images, and when and how they fail. To bridge this gap,

  • Susceptible-infected-spreading-based network embedding in static and temporal networks
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-10-16
    Xiu-Xiu Zhan, Ziyu Li, Naoki Masuda, Petter Holme, Huijuan Wang

    Link prediction can be used to extract missing information, identify spurious interactions as well as forecast network evolution. Network embedding is a methodology to assign coordinates to nodes in a low-dimensional vector space. By embedding nodes into vectors, the link prediction problem can be converted into a similarity comparison task. Nodes with similar embedding vectors are more likely to be

  • Modeling and predicting evacuation flows during hurricane Irma
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-09-29
    Lingzi Hong, Vanessa Frias-Martinez

    Evacuations are a common practice to mitigate the potential risks and damages made by natural disasters. However, without proper coordination and management, evacuations can be inefficient and cause negative impact. Local governments and organizations need to have a better understanding of how the population responds to disasters and evacuation recommendations so as to enhance their disaster management

  • Early detection of influenza outbreak using time derivative of incidence.
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-09-11
    Woo-Sik Son,Ji-Eun Park,Okyu Kwon

    For mitigation strategies of an influenza outbreak, it can be helpful to understand the characteristics of regional and age-group-specific spread. In South Korea, however, there has been no official statistic related to it. In this study, we extract the time series of influenza incidence from National Health Insurance Service claims database, which consists of all medical and prescription drug-claim

  • Estimating educational outcomes from students’ short texts on social media
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-09-01
    Ivan Smirnov

    Digital traces have become an essential source of data in social sciences because they provide new insights into human behavior and allow studies to be conducted on a larger scale. One particular area of interest is the estimation of various users’ characteristics from their texts on social media. Although it has been established that basic categorical attributes could be effectively predicted from

  • Enriching feature engineering for short text samples by language time series analysis
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-08-31
    Yichen Tang; Kelly Blincoe; Andreas W. Kempa-Liehr

    In this case study, we are extending feature engineering approaches for short text samples by integrating techniques which have been introduced in the context of time series classification and signal processing. The general idea of the presented feature engineering approach is to tokenize the text samples under consideration and map each token to a number, which measures a specific property of the

  • Estimating community feedback effect on topic choice in social media with predictive modeling
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-08-31
    David Ifeoluwa Adelani; Ryota Kobayashi; Ingmar Weber; Przemyslaw A. Grabowicz

    Social media users post content on various topics. A defining feature of social media is that other users can provide feedback—called community feedback—to their content in the form of comments, replies, and retweets. We hypothesize that the amount of received feedback influences the choice of topics on which a social media user posts. However, it is challenging to test this hypothesis as user heterogeneity

  • A weighted travel time index based on data from Uber Movement
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-08-08
    Renato S. Vieira; Eduardo A. Haddad

    In this paper, we combine data from Uber Movement and from a representative household travel survey to constructs a weighted travel time index for the Metropolitan Region of São Paulo. The index is calculated based on the average travel time of Uber trips taken between each pair of traffic zone and in each hour between January 1st, 2016 to December 31, 2018. The index is weighted based on trips reported

  • Mapping socioeconomic indicators using social media advertising data
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-07-29
    Masoomali Fatehkia; Isabelle Tingzon; Ardie Orden; Stephanie Sy; Vedran Sekara; Manuel Garcia-Herranz; Ingmar Weber

    The United Nations Sustainable Development Goals (SDGs) are a global consensus on the world’s most pressing challenges. They come with a set of 232 indicators against which countries should regularly monitor their progress, ensuring that everyone is represented in up-to-date data that can be used to make decisions to improve people’s lives. However, existing data sources to measure progress on the

  • Efficient algorithm to compute Markov transitional probabilities for a desired PageRank
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-07-29
    Gábor Berend

    We propose an efficient algorithm to learn the transition probabilities of a Markov chain in a way that its weighted PageRank scores meet some predefined target values. Our algorithm does not require any additional information about the nodes and the edges in the form of features, i.e., it solely considers the network topology for calibrating the transition probabilities of the Markov chain for obtaining

  • The Butterfly “Affect”: impact of development practices on cryptocurrency prices
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-07-23
    Silvia Bartolucci; Giuseppe Destefanis; Marco Ortu; Nicola Uras; Michele Marchesi; Roberto Tonelli

    The network of developers in distributed ledgers and blockchains open source projects is essential to maintaining the platform: understanding the structure of their exchanges, analysing their activity and its quality (e.g. issues resolution times, politeness in comments) is important to determine how “healthy” and efficient a project is. The quality of a project affects the trust in the platform, and

  • Segregated interactions in urban and online space
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-07-10
    Xiaowen Dong; Alfredo J. Morales; Eaman Jahani; Esteban Moro; Bruno Lepri; Burcin Bozkaya; Carlos Sarraute; Yaneer Bar-Yam; Alex Pentland

    Urban income segregation is a widespread phenomenon that challenges societies across the globe. Classical studies on segregation have largely focused on the geographic distribution of residential neighborhoods rather than on patterns of social behaviors and interactions. In this study, we analyze segregation in economic and social interactions by observing credit card transactions and Twitter mentions

  • Temporal social network reconstruction using wireless proximity sensors: model selection and consequences
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-07-08
    Sicheng Dai; Hélène Bouchet; Aurélie Nardy; Eric Fleury; Jean-Pierre Chevrot; Márton Karsai

    The emerging technologies of wearable wireless devices open entirely new ways to record various aspects of human social interactions in a broad range of settings. Such technologies allow to log the temporal dynamics of face-to-face interactions by detecting the physical proximity of participants. However, despite the wide usage of this technology and the collected datasets, precise reconstruction methods

  • Which politicians receive abuse? Four factors illuminated in the UK general election 2019
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-07-02
    Genevieve Gorrell; Mehmet E. Bakir; Ian Roberts; Mark A. Greenwood; Kalina Bontcheva

    The 2019 UK general election took place against a background of rising online hostility levels toward politicians, and concerns about the impact of this on democracy, as a record number of politicians cited the abuse they had been receiving as a reason for not standing for re-election. We present a four-factor framework in understanding who receives online abuse and why. The four factors are prominence

  • Economic outcomes predicted by diversity in cities
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-06-24
    Shi Kai Chong; Mohsen Bahrami; Hao Chen; Selim Balcisoy; Burcin Bozkaya; Alex ‘Sandy’ Pentland

    Much recent work has illuminated the growth, innovation, and prosperity of entire cities, but there is relatively less evidence concerning the growth and prosperity of individual neighborhoods. In this paper we show that diversity of amenities within a city neighborhood, computed from openly available points of interest on digital maps, accurately predicts human mobility (“flows”) between city neighborhoods

  • Hypernetwork science via high-order hypergraph walks
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-06-10
    Sinan G. Aksoy; Cliff Joslyn; Carlos Ortiz Marrero; Brenda Praggastis; Emilie Purvine

    We propose high-order hypergraph walks as a framework to generalize graph-based network science techniques to hypergraphs. Edge incidence in hypergraphs is quantitative, yielding hypergraph walks with both length and width. Graph methods which then generalize to hypergraphs include connected component analyses, graph distance-based metrics such as closeness centrality, and motif-based measures such

  • Efficient modeling of higher-order dependencies in networks: from algorithm to application for anomaly detection
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-06-09
    Mandana Saebi; Jian Xu; Lance M. Kaplan; Bruno Ribeiro; Nitesh V. Chawla

    Complex systems, represented as dynamic networks, comprise of components that influence each other via direct and/or indirect interactions. Recent research has shown the importance of using Higher-Order Networks (HONs) for modeling and analyzing such complex systems, as the typical Markovian assumption in developing the First Order Network (FON) can be limiting. This higher-order network representation

  • In search of art: rapid estimates of gallery and museum visits using Google Trends
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-06-05
    Federico Botta; Tobias Preis; Helen Susannah Moat

    Measuring collective human behaviour has traditionally been a time-consuming and expensive process, impairing the speed at which data can be made available to decision makers in policy. Can data generated through widespread use of online services help provide faster insights? Here, we consider an example relating to policymaking for culture and the arts: publicly funded museums and galleries in the

  • PepMusic: motivational qualities of songs for daily activities
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-05-24
    Yongsung Kim; Luca Maria Aiello; Daniele Quercia

    Music can motivate many daily activities as it can regulate mood, increase productivity and sports performance, and raise spirits. However, we know little about how to recommend songs that are motivational for people given their contexts and activities. As a first step towards dealing with this issue, we adopt a theory-driven approach and operationalize the Brunel Music Rating Inventory (BMRI) to identify

  • Public debate in the media matters: evidence from the European refugee crisis
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-05-13
    Caleb M. Koch; Izabela Moise; Dirk Helbing; Karsten Donnay

    In this paper, we take a novel approach to study the empirical relationship between public debate in the media and asylum acceptance rates in Europe from 2002–2016. In theory, an asylum seeker should experience the same likelihood of being granted refugee status from each of the 20 European countries we study. Yet, in practice, acceptance rates vary widely for nearly every asylum country of origin

  • Comparative analysis of layered structures in empirical investor networks and cellphone communication networks
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-05-07
    Peng Wang; Jun-Chao Ma; Zhi-Qiang Jiang; Wei-Xing Zhou; Didier Sornette

    Empirical investor networks (EIN) proposed by Ozsoylev et al. are assumed to capture the information spreading path among investors. Here, we perform a comparative analysis between the EIN and the cellphone communication networks (CN) to test whether EIN is an information exchanging network from the perspective of the layer structures of ego networks. We employ two clustering algorithms (k-means algorithm

  • News and the city: understanding online press consumption patterns through mobile data
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-04-29
    Salvatore Vilella; Daniela Paolotti; Giancarlo Ruffo; Leo Ferres

    The always increasing mobile connectivity affects every aspect of our daily lives, including how and when we keep ourselves informed and consult news media. By studying a DPI (deep packet inspection) dataset, provided by one of the major Chilean telecommunication companies, we investigate how different cohorts of the population of Santiago De Chile consume news media content through their smartphones

  • Success and luck in creative careers
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-04-28
    Milán Janosov; Federico Battiston; Roberta Sinatra

    Luck is considered a crucial ingredient to achieve impact in all creative domains, despite their diversity. For instance, in science, the movie industry, music, and art, the occurrence of the highest impact work and a hot streak within a creative career are very difficult to predict. Are there domains that are more prone to luck than others? Here, we provide new insights on the role of randomness in

  • Correction to: Gendered behavior as a disadvantage in open source software development
    EPJ Data Sci. (IF 2.873) Pub Date : 2019-09-19
    Balazs Vedres, Orsolya Vasarhelyi

    Following publication of the original article [1], we have been notified that one more affiliation of the corresponding author is missing. Currently Balasz Vedres affiliation is: 1 Oxford Internet Institute, University of Oxford, Oxford, United Kingdom It should be: 1 Oxford Internet Institute, University of Oxford, Oxford, United Kingdom; 2 Department of Network and Data Science, Central European

  • A new set of cluster driven composite development indicators
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-04-10
    Anshul Verma; Orazio Angelini; Tiziana Di Matteo

    Composite development indicators used in policy making often subjectively aggregate a restricted set of indicators. We show, using dimensionality reduction techniques, including Principal Component Analysis (PCA) and for the first time information filtering and hierarchical clustering, that these composite indicators miss key information on the relationship between different indicators. In particular

  • Fake news propagates differently from real news even at early stages of spreading
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-04-03
    Zilong Zhao; Jichang Zhao; Yukie Sano; Orr Levy; Hideki Takayasu; Misako Takayasu; Daqing Li; Junjie Wu; Shlomo Havlin

    Social media can be a double-edged sword for society, either as a convenient channel exchanging ideas or as an unexpected conduit circulating fake news through a large population. While existing studies of fake news focus on theoretical modeling of propagation or identification methods based on machine learning, it is important to understand the realistic propagation mechanisms between theoretical

  • Measuring the effect of node aggregation on community detection
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-03-11
    Yérali Gandica; Adeline Decuyper; Christophe Cloquet; Isabelle Thomas; Jean-Charles Delvenne

    Many times the nodes of a complex network, whether deliberately or not, are aggregated for technical, ethical, legal limitations or privacy reasons. A common example is the geographic position: one may uncover communities in a network of places, or of individuals identified with their typical geographical position, and then aggregate these places into larger entities, such as municipalities, thus obtaining

  • Measuring and mitigating behavioural segregation using Call Detail Records
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-03-06
    Daniel Rhoads; Ivan Serrano; Javier Borge-Holthoefer; Albert Solé-Ribalta

    The overwhelming amounts of data we generate in our daily routine and in social networks has been crucial for the understanding of various social and economic factors. The use of this data represents a low-cost alternative source of information in parallel to census data and surveys. Here, we advocate for such an approach to assess and alleviate the segregation of Syrian refugees in Turkey. Using a

  • The shocklet transform: a decomposition method for the identification of local, mechanism-driven dynamics in sociotechnical time series
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-02-07
    David Rushing Dewhurst; Thayer Alshaabi; Dilan Kiley; Michael V. Arnold; Joshua R. Minot; Christopher M. Danforth; Peter Sheridan Dodds

    We introduce a qualitative, shape-based, timescale-independent time-domain transform used to extract local dynamics from sociotechnical time series—termed the Discrete Shocklet Transform (DST)—and an associated similarity search routine, the Shocklet Transform And Ranking (STAR) algorithm, that indicates time windows during which panels of time series display qualitatively-similar anomalous behavior

  • Novelty and influence of creative works, and quantifying patterns of advances based on probabilistic references networks
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-01-30
    Doheum Park; Juhan Nam; Juyong Park

    Recent advances in the quantitative, computational methodology for the modeling and analysis of heterogeneous large-scale data are leading to new opportunities for understanding human behaviors and faculties, including creativity that drives creative enterprises such as science. While innovation is crucial for novel and influential achievements, quantifying these qualities in creative works remains

  • The individual dynamics of affective expression on social media
    EPJ Data Sci. (IF 2.873) Pub Date : 2020-01-09
    Max Pellert; Simon Schweighofer; David Garcia

    Understanding the temporal dynamics of affect is crucial for our understanding human emotions in general. In this study, we empirically test a computational model of affective dynamics by analyzing a large-scale dataset of Facebook status updates using text analysis techniques. Our analyses support the central assumptions of our model: After stimulation, affective states, quantified as valence and

  • The higher education space: connecting degree programs from individuals’ choices
    EPJ Data Sci. (IF 2.873) Pub Date : 2019-12-30
    Cristian Candia; Sara Encarnação; Flávio L. Pinheiro

    Data on the applicants’ revealed preferences when entering higher education is used as a proxy to build the Higher Education Space (HES) of Portugal (2008–2015) and Chile (2006–2017). The HES is a network that connects pairs of degree programs according to their co-occurrence in the applicants’ preferences. We show that both HES network structures reveal the existence of positive assortment in features

  • What did you see? A study to measure personalization in Google’s search engine
    EPJ Data Sci. (IF 2.873) Pub Date : 2019-12-16
    Tobias D. Krafft; Michael Gamer; Katharina A. Zweig

    In this paper we present the results of the project “#Datenspende” where during the German election in 2017 more than 4000 people contributed their search results regarding keywords connected to the German election campaign.Analyzing the donated result lists we prove, that the room for personalization of the search results is very small. Thus the opportunity for the effect mentioned in Eli Pariser’s

  • Following the footsteps of giants: modeling the mobility of historically notable individuals using Wikipedia
    EPJ Data Sci. (IF 2.873) Pub Date : 2019-12-12
    Lorenzo Lucchini; Sara Tonelli; Bruno Lepri

    The steady growth of digitized historical information is continuously stimulating new different approaches to the fields of Digital Humanities and Computational Social Science. In this work we use Natural Language Processing techniques to retrieve large amounts of historical information from Wikipedia. In particular, the pages of a set of historically notable individuals are processed to catch the

  • Gravity law in the Chinese highway freight transportation networks
    EPJ Data Sci. (IF 2.873) Pub Date : 2019-12-12
    Li Wang; Jun-Chao Ma; Zhi-Qiang Jiang; Wanfeng Yan; Wei-Xing Zhou

    The gravity law has been documented in many socioeconomic networks, which states that the flow between two nodes positively correlates with the strengths of the nodes and negatively correlates with the distance between the two nodes. However, such research on highway freight transportation networks (HFTNs) is rare. We construct the directed and undirected highway freight transportation networks between

  • Quantifying echo chamber effects in information spreading over political communication networks
    EPJ Data Sci. (IF 2.873) Pub Date : 2019-12-09
    Wesley Cota; Silvio C. Ferreira; Romualdo Pastor-Satorras; Michele Starnini

    Echo chambers in online social networks, in which users prefer to interact only with ideologically-aligned peers, are believed to facilitate misinformation spreading and contribute to radicalize political discourse. In this paper, we gauge the effects of echo chambers in information spreading phenomena over political communication networks. Mining 12 million Twitter messages, we reconstruct a network

  • From individual to collective behaviours: exploring population heterogeneity of human mobility based on social media data
    EPJ Data Sci. (IF 2.873) Pub Date : 2019-11-14
    Yuan Liao; Sonia Yeh; Gustavo S. Jeuken

    This paper examines the population heterogeneity of travel behaviours from a combined perspective of individual actors and collective behaviours. We use a social media dataset of 652,945 geotagged tweets generated by 2,933 Swedish Twitter users covering an average time span of 3.6 years. No explicit geographical boundaries, such as national borders or administrative boundaries, are applied to the data

  • Mapping the physics research space: a machine learning approach
    EPJ Data Sci. (IF 2.873) Pub Date : 2019-11-06
    Matteo Chinazzi; Bruno Gonçalves; Qian Zhang; Alessandro Vespignani

    Scientific discoveries do not occur in vacuum but rather by connecting existing pieces of knowledge in new and creative ways. Mapping the relation and structure of scientific knowledge is therefore central to our understanding of the dynamics of scientific production. Here we introduce a new approach to generate scientific knowledge maps based on a machine learning approach that, starting from the

  • Assessing the risk of default propagation in interconnected sectoral financial networks
    EPJ Data Sci. (IF 2.873) Pub Date : 2019-11-04
    Adrià Barja; Alejandro Martínez; Alex Arenas; Pablo Fleurquin; Jordi Nin; José J. Ramasco; Elena Tomás

    Systemic risk of financial institutions and sectoral companies relies on their inter-dependencies. The inter-connectivity of the financial networks has proven to be crucial to understand the propagation of default, as it plays a central role to assess the impact of single default events in the full system. Here, we take advantage of complex network theory to shed light on the mechanisms behind default

  • Knowledge-based biomedical Data Science.
    EPJ Data Sci. (IF 2.873) Pub Date : 2017-01-01
    Lawrence E Hunter

    Computational manipulation of knowledge is an important, and often under-appreciated, aspect of biomedical Data Science. The first Data Science initiative from the US National Institutes of Health was entitled "Big Data to Knowledge (BD2K)." The main emphasis of the more than $200M allocated to that program has been on "Big Data;" the "Knowledge" component has largely been the implicit assumption that

  • Success in books: predicting book sales before publication
    EPJ Data Sci. (IF 2.873) Pub Date : 2019-10-17
    Xindi Wang; Burcu Yucesoy; Onur Varol; Tina Eliassi-Rad; Albert-László Barabási

    Reading remains a preferred leisure activity fueling an exceptionally competitive publishing market: among more than three million books published each year, only a tiny fraction are read widely. It is largely unpredictable, however, which book will that be, and how many copies it will sell. Here we aim to unveil the features that affect the success of books by predicting a book’s sales prior to its

  • Complete trajectory reconstruction from sparse mobile phone data
    EPJ Data Sci. (IF 2.873) Pub Date : 2019-10-12
    Guangshuo Chen; Aline Carneiro Viana; Marco Fiore; Carlos Sarraute

    Mobile phone data are a popular source of positioning information in many recent studies that have largely improved our understanding of human mobility. These data consist of time-stamped and geo-referenced communication events recorded by network operators, on a per-subscriber basis. They allow for unprecedented tracking of populations of millions of individuals over long periods that span months

  • Identifying the most influential roads based on traffic correlation networks
    EPJ Data Sci. (IF 2.873) Pub Date : 2019-09-18
    Shengmin Guo; Dong Zhou; Jingfang Fan; Qingfeng Tong; Tongyu Zhu; Weifeng Lv; Daqing Li; Shlomo Havlin

    Prediction of traffic congestion is one of the core issues in the realization of smart traffic. Accurate prediction depends on understanding of interactions and correlations between different city locations. While many methods merely consider the spatio-temporal correlation between two locations, here we propose a new approach of capturing the correlation network in a city based on realtime traffic

  • Explore with caution: mapping the evolution of scientific interest in physics
    EPJ Data Sci. (IF 2.873) Pub Date : 2019-09-11
    Alberto Aleta; Sandro Meloni; Nicola Perra; Yamir Moreno

    In the book The Essential Tension (1979) Thomas Kuhn described the conflict between tradition and innovation in scientific research—i.e., the desire to explore new promising areas, counterposed to the need to capitalize on the work done in the past. While it is probable that along their careers many scientists felt this tension, only few works have tried to quantify it. Here, we address this question

  • Dissecting global air traffic data to discern different types and trends of transnational human mobility
    EPJ Data Sci. (IF 2.873) Pub Date : 2019-08-30
    Lorenzo Gabrielli; Emanuel Deutschmann; Fabrizio Natale; Ettore Recchi; Michele Vespe

    Human mobility across national borders is a key phenomenon of our time. At the global scale, however, we still know relatively little about the structure and nature of such transnational movements. This study uses a large dataset on monthly air passenger traffic between 239 countries worldwide from 2010 to 2018 to gain new insights into (a) mobility trends over time and (b) types of mobility. A time

  • Gendered behavior as a disadvantage in open source software development
    EPJ Data Sci. (IF 2.873) Pub Date : 2019-07-06
    Balazs Vedres; Orsolya Vasarhelyi

    Women are severely marginalized in software development, especially in open source. In this article we argue that disadvantage is more due to gendered behavior than to categorical discrimination: women are at a disadvantage because of what they do, rather than because of who they are. Using data on entire careers of users from GitHub.com, we develop a measure to capture the gendered pattern of behavior:

  • Testing Heaps’ law for cities using administrative and gridded population data sets
    EPJ Data Sci. (IF 2.873) Pub Date : 2019-07-05
    Filippo Simini; Charlotte James

    Since 2008 the number of individuals living in urban areas has surpassed that of rural areas and in the next decades urbanisation is expected to further increase, especially in developing countries. A country’s urbanisation depends both on the distribution of city sizes, describing the fraction of cities with a given population (or area), and the overall number of cities in the country. Here we present

  • Predicting and explaining behavioral data with structured feature space decomposition
    EPJ Data Sci. (IF 2.873) Pub Date : 2019-06-27
    Peter G. Fennell; Zhiya Zuo; Kristina Lerman

    Modeling human behavioral data is challenging due to its scale, sparseness (few observations per individual), heterogeneity (differently behaving individuals), and class imbalance (few observations of the outcome of interest). An additional challenge is learning an interpretable model that not only accurately predicts outcomes, but also identifies important factors associated with a given behavior

  • The dynamics of collective social behavior in a crowd controlled game
    EPJ Data Sci. (IF 2.873) Pub Date : 2019-06-07
    Alberto Aleta; Yamir Moreno

    Despite many efforts, the behavior of a crowd is not fully understood. The advent of modern communication means has made it an even more challenging problem, as crowd dynamics could be driven by both human-to-human and human-technology interactions. Here, we study the dynamics of a crowd controlled game (Twitch Plays Pokémon), in which nearly a million players participated during more than two weeks

  • Corporate payments networks and credit risk rating
    EPJ Data Sci. (IF 2.873) Pub Date : 2019-06-01
    Elisa Letizia; Fabrizio Lillo

    Aggregate and systemic risk in complex systems are emergent phenomena depending on two properties: the idiosyncratic risk of the elements and the topology of the network of interactions among them. While a significant attention has been given to aggregate risk assessment and risk propagation once the above two properties are given, less is known about how the risk is distributed in the network and

  • Cities of a feather flock together: a study on the synchronization of communication between Italian cities
    EPJ Data Sci. (IF 2.873) Pub Date : 2019-05-29
    Lorenzo Candeago; Giulia Bertagnolli; Paolo Bosetti; Michele Vescovi; Francesco Sacco; Bruno Lepri

    Due to the rise of communication technologies and economic globalization, modern large cities are becoming more and more interconnected and this phenomenon leads to an increasing synchronization in activities and communication patterns. In our work, we explore the communication synchronization between 76 Italian cities of different sizes by using mobile phone data. Our results show that both the spatial

  • Reciprocity and impact in academic careers
    EPJ Data Sci. (IF 2.873) Pub Date : 2019-05-29
    Weihua Li; Tomaso Aste; Fabio Caccioli; Giacomo Livan

    The growing importance of citation-based bibliometric indicators in shaping the prospects of academic careers incentivizes scientists to boost the numbers of citations they receive. Whereas the exploitation of self-citations has been extensively documented, the impact of reciprocated citations has not yet been studied. We study reciprocity in a citation network of authors, and compare it with the average

  • Quantifying human mobility resilience to extreme events using geo-located social media data
    EPJ Data Sci. (IF 2.873) Pub Date : 2019-05-22
    Kamol Chandra Roy; Manuel Cebrian; Samiul Hasan

    Mobility is one of the fundamental requirements of human life with significant societal impacts including productivity, economy, social wellbeing, adaptation to a changing climate, and so on. Although human movements follow specific patterns during normal periods, there are limited studies on how such patterns change due to extreme events. To quantify the impacts of an extreme event to human movements

  • Understanding news outlets’ audience-targeting patterns
    EPJ Data Sci. (IF 2.873) Pub Date : 2019-05-14
    Erick Elejalde; Leo Ferres; Rossano Schifanella

    The power of the press to shape the informational landscape of a population is unparalleled, even now in the era of democratic access to all information outlets. However, it is known that news outlets (particularly more traditional ones) tend to discriminate who they want to reach, and who to leave aside. In this work, we attempt to shed some light on the audience targeting patterns of newspapers,

  • Psychology and morality of political extremists: evidence from Twitter language analysis of alt-right and Antifa
    EPJ Data Sci. (IF 2.873) Pub Date : 2019-05-14
    Meysam Alizadeh; Ingmar Weber; Claudio Cioffi-Revilla; Santo Fortunato; Michael Macy

    The recent rise of the political extremism in Western countries has spurred renewed interest in the psychological and moral appeal of political extremism. Empirical support for the psychological explanation using surveys has been limited by lack of access to extremist groups, while field studies have missed psychological measures and failed to compare extremists with contrast groups. We revisit the

  • Centrality in modular networks
    EPJ Data Sci. (IF 2.873) Pub Date : 2019-05-09
    Zakariya Ghalmane; Mohammed El Hassouni; Chantal Cherifi; Hocine Cherifi

    Identifying influential nodes in a network is a fundamental issue due to its wide applications, such as accelerating information diffusion or halting virus spreading. Many measures based on the network topology have emerged over the years to identify influential nodes such as Betweenness, Closeness, and Eigenvalue centrality. However, although most real-world networks are made of groups of tightly

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