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  1. 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. Sp...

    Authors: Alexander Veremyev, Alexander Semenov, Eduardo L. Pasiliao and Vladimir Boginski

    Citation: Applied Network Science 2019 4:104

    Content type: Research

    Published on:

  2. 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. ...

    Authors: Evelin Berekméri, Imre Derényi and Anna Zafeiris

    Citation: Applied Network Science 2019 4:101

    Content type: Research

    Published on:

  3. 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 immediat...

    Authors: Hamidreza Mahyar, Rouzbeh Hasheminezhad and H Eugene Stanley

    Citation: Applied Network Science 2019 4:100

    Content type: Research

    Published on:

  4. 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...

    Authors: Nicole Balashov, Reuven Cohen, Avieli Haber, Michael Krivelevich and Simi Haber

    Citation: Applied Network Science 2019 4:99

    Content type: Research

    Published on:

  5. Recent disasters have shown the existence of large variance in recovery trajectories across cities that have experienced similar damage levels. Case studies of such events reveal the high complexity of the rec...

    Authors: Takahiro Yabe, Satish V. Ukkusuri and P. Suresh C. Rao

    Citation: Applied Network Science 2019 4:98

    Content type: Research

    Published on:

  6. 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 ...

    Authors: Victor H. Masias, Tobias Hecking, Fernando Crespo and H. Ulrich Hoppe

    Citation: Applied Network Science 2019 4:96

    Content type: Research

    Published on:

  7. 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 compl...

    Authors: Antonio Maria Fiscarelli, Matthias R. Brust, Grégoire Danoy and Pascal Bouvry

    Citation: Applied Network Science 2019 4:95

    Content type: Research

    Published on:

  8. 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...

    Authors: Long Ma, Qiang Liu and Piet Van Mieghem

    Citation: Applied Network Science 2019 4:93

    Content type: Research

    Published on:

  9. 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 vie...

    Authors: Leonardo Bacelar Lima Santos, Luiz Max Carvalho, Wilson Seron, Flávio C. Coelho, Elbert E. Macau, Marcos G. Quiles and Antônio M. V. Monteiro

    Citation: Applied Network Science 2019 4:91

    Content type: Research

    Published on:

  10. During a single heartbeat, muscle cells in the heart contract and relax. Under healthy conditions, the behaviour of these muscle cells is almost identical from one beat to the next. However, this regular rhyth...

    Authors: Yi Ming Lai, Joshua Veasy, Stephen Coombes and Rüdiger Thul

    Citation: Applied Network Science 2019 4:90

    Content type: Research

    Published on:

  11. This paper details a network-based analysis of the spreading of rodent infestations through a city under varying conditions. Models of two very different cities, Tulsa, OK, USA and Providence, RI, USA, are cre...

    Authors: Dalton Brooks and John Matta

    Citation: Applied Network Science 2019 4:89

    Content type: Research

    Published on:

  12. The success of graph embeddings or nodrepresentation learning in a variety of downstream tasks, such as node classification, link prediction, and recommendation systems, has led to their popularity in recent y...

    Authors: Saba A. Al-Sayouri, Danai Koutra, Evangelos E. Papalexakis and Sarah S. Lam

    Citation: Applied Network Science 2019 4:88

    Content type: Research

    Published on:

  13. We derive complexity estimates for two classes of deterministic networks: the Boolean networks S(Bn, m), which compute the Boolean vector-functions Bn, m, and the classes of graphs ...

    Authors: Alexander Goryashko, Leonid Samokhine and Pavel Bocharov

    Citation: Applied Network Science 2019 4:87

    Content type: Research

    Published on:

  14. Most real-world graphs collected from the Web like Web graphs and social network graphs are partially discovered or crawled. This leads to inaccurate estimates of graph properties based on link analysis such as P...

    Authors: Helge Holzmann, Avishek Anand and Megha Khosla

    Citation: Applied Network Science 2019 4:86

    Content type: Research

    Published on:

  15. Nowadays, research has found a strong relationship between genomic status and occurrence of disease. Cancer is one of the most common diseases that leads to a high annual mortality rate worldwide, and the dise...

    Authors: Seyed Mohammad Razavi, Farzaneh Rami, Seyede Houri Razavi and Changiz Eslahchi

    Citation: Applied Network Science 2019 4:83

    Content type: Research

    Published on:

  16. A main challenge in mining network-based data is finding effective ways to represent or encode graph structures so that it can be efficiently exploited by machine learning algorithms. Several methods have focu...

    Authors: Leonardo Gutiérrez-Gómez and Jean-Charles Delvenne

    Citation: Applied Network Science 2019 4:82

    Content type: Research

    Published on:

  17. The existence of groups of nodes with common characteristics and the relationships between these groups are important factors influencing the structures of social, technological, biological, and other networks...

    Authors: Milos Kudelka, Eliska Ochodkova, Sarka Zehnalova and Jakub Plesnik

    Citation: Applied Network Science 2019 4:81

    Content type: Research

    Published on:

  18. Similarity measures are used extensively in machine learning and data science algorithms. The newly proposed graph Relative Hausdorff (RH) distance is a lightweight yet nuanced similarity measure for quantifyi...

    Authors: Sinan G. Aksoy, Kathleen E. Nowak, Emilie Purvine and Stephen J. Young

    Citation: Applied Network Science 2019 4:80

    Content type: Research

    Published on:

  19. This study examines the interface of three elements during co-contagion diffusion: the synergy between contagions, the dormancy rate of each individual contagion, and the multiplex network topology. Dormancy is d...

    Authors: Ho-Chun Herbert Chang and Feng Fu

    Citation: Applied Network Science 2019 4:78

    Content type: Research

    Published on:

  20. Recent neural networks designed to operate on graph-structured data have proven effective in many domains. These graph neural networks often diffuse information using the spatial structure of the graph. We pro...

    Authors: Stefan Dernbach, Arman Mohseni-Kabir, Siddharth Pal, Miles Gepner and Don Towsley

    Citation: Applied Network Science 2019 4:76

    Content type: Research

    Published on:

  21. Evaluating scientists based on their scientific production is a controversial topic. Nevertheless, bibliometrics and algorithmic approaches can assist traditional peer review in numerous tasks, such as attribu...

    Authors: Jorge Silva, David Aparício and Fernando Silva

    Citation: Applied Network Science 2019 4:74

    Content type: Research

    Published on:

  22. In this paper, we investigate the relationship between the coupling strengths and the extensive behaviour of the sum of the positive Lyapunov exponents of multiplex networks formed by coupled dynamical units. ...

    Authors: Maria Angélica Araujo and Murilo S. Baptista

    Citation: Applied Network Science 2019 4:73

    Content type: Research

    Published on:

  23. The friendship paradox is the observation that friends of individuals tend to have more friends or be more popular than the individuals themselves. In this work, we first study local metrics to capture the str...

    Authors: Siddharth Pal, Feng Yu, Yitzchak Novick, Ananthram Swami and Amotz Bar-Noy

    Citation: Applied Network Science 2019 4:71

    Content type: Research

    Published on:

  24. The detection and prediction of risk in financial markets is one of the main challenges of economic forecasting, and draws much attention from the scientific community. An even more challenging task is the pre...

    Authors: Jingfang Fan, Keren Cohen, Louis M. Shekhtman, Sibo Liu, Jun Meng, Yoram Louzoun and Shlomo Havlin

    Citation: Applied Network Science 2019 4:69

    Content type: Research

    Published on:

  25. We propose sequence-to-sequence architectures for graph representation learning in both supervised and unsupervised regimes. Our methods use recurrent neural networks to encode and decode information from grap...

    Authors: Aynaz Taheri, Kevin Gimpel and Tanya Berger-Wolf

    Citation: Applied Network Science 2019 4:68

    Content type: Research

    Published on:

  26. In this paper, we present algorithms that learn and update temporal node embeddings on the fly for tracking and measuring node similarity over time in graph streams. Recently, several representation learning m...

    Authors: Ferenc Béres, Domokos M. Kelen, Róbert Pálovics and András A. Benczúr

    Citation: Applied Network Science 2019 4:64

    Content type: Research

    Published on:

  27. Information networks are becoming increasingly popular to capture complex relationships across various disciplines, such as social networks, citation networks, and biological networks. The primary challenge in...

    Authors: Mehmet E. Aktas, Esra Akbas and Ahmed El Fatmaoui

    Citation: Applied Network Science 2019 4:61

    Content type: Review

    Published on:

  28. This paper examines the process of protest claim-making by reconstructing the semantic structure of online communication that took place prior to the first street event of a protest. Topic networks are identif...

    Authors: Eunkyung Song

    Citation: Applied Network Science 2019 4:60

    Content type: Research

    Published on:

  29. PageRank for Semi-Supervised Learning has shown to leverage data structures and limited tagged examples to yield meaningful classification. Despite successes, classification performance can still be improved, ...

    Authors: Esteban Bautista, Patrice Abry and Paulo Gonçalves

    Citation: Applied Network Science 2019 4:57

    Content type: Research

    Published on:

  30. The availability of the entire Bitcoin transaction history, stored in its public blockchain, offers interesting opportunities for analysing the transaction graph to obtain insight on users behaviour. This pape...

    Authors: Damiano Di Francesco Maesa, Andrea Marino and Laura Ricci

    Citation: Applied Network Science 2019 4:56

    Content type: Research

    Published on:

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