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  1. The retweet is a characteristic mechanism of several social network services/social media, such as Facebook, Twitter, and Weibo. By retweeting tweet, users can share an article with their friends and followers...

    Authors: Yizhou Yan, Fujio Toriumi and Toshiharu Sugawara

    Citation: Computational Social Networks 2021 8:18

    Content type: Research

    Published on:

  2. Influence maximization is the problem of trying to maximize the number of influenced nodes by selecting optimal seed nodes, given that influencing these nodes is costly. Due to the probabilistic nature of the ...

    Authors: Mehrdad Agha Mohammad Ali Kermani, Reza Ghesmati and Mir Saman Pishvaee

    Citation: Computational Social Networks 2021 8:17

    Content type: Research

    Published on:

  3. Digital social networks have become an essential source of information because celebrities use them to share their opinions, ideas, thoughts, and feelings. This makes digital social networks one of the preferr...

    Authors: Luis G. Moreno-Sandoval, Alexandra Pomares-Quimbaya and Jorge A. Alvarado-Valencia

    Citation: Computational Social Networks 2021 8:16

    Content type: Research

    Published on:

  4. Socio-technical systems usually consist of many intertwined networks, each connecting different types of objects or actors through a variety of means. As these networks are co-dependent, one can take advantage...

    Authors: Hong-Lan Botterman and Robin Lamarche-Perrin

    Citation: Computational Social Networks 2021 8:15

    Content type: Research

    Published on:

  5. The ability for people and organizations to connect in the digital age has allowed the growth of networks that cover an increasing proportion of human interactions. The research community investigating network...

    Authors: Alexander V. Mantzaris, Douglas Chiodini and Kyle Ricketson

    Citation: Computational Social Networks 2021 8:12

    Content type: Research

    Published on:

  6. Migration, and urbanization as its consequence, is among the most intricate political and scientific topics, predicted to have huge effects on human lives in the near future. Thus being said, previous works ha...

    Authors: Dino Pitoski, Thomas J. Lampoltshammer and Peter Parycek

    Citation: Computational Social Networks 2021 8:10

    Content type: Research

    Published on:

  7. This study examines the influence maximization (IM) problem via information cascades within random graphs, the topology of which dynamically changes due to the uncertainty of user behavior. This study leverage...

    Authors: Mengnan Chen, Qipeng P. Zheng, Vladimir Boginski and Eduardo L. Pasiliao

    Citation: Computational Social Networks 2021 8:9

    Content type: Research

    Published on:

  8. Using the headers of scientific papers, we have built multilayer networks of entities involved in research namely: authors, laboratories, and institutions. We have analyzed some properties of such networks bui...

    Authors: Ghislain Romaric Meleu and Paulin Yonta Melatagia

    Citation: Computational Social Networks 2021 8:8

    Content type: Research

    Published on:

  9. Social media networks have been playing an increasingly more important role for both socialization and information diffusion. Political campaign can gain more supporters by attracting more mass attention and i...

    Authors: Guanxiang Yun, Qipeng P. Zheng, Vladimir Boginski and Eduardo L. Pasiliao

    Citation: Computational Social Networks 2021 8:7

    Content type: Research

    Published on:

  10. In computer science, there exist a large number of optimization problems defined on graphs, that is to find a best node state configuration or a network structure, such that the designed objective function is ...

    Authors: Yaoxin Li, Jing Liu, Guozheng Lin, Yueyuan Hou, Muyun Mou and Jiang Zhang

    Citation: Computational Social Networks 2021 8:5

    Content type: Research

    Published on:

  11. Centrality measures have been proved to be a salient computational science tool for analyzing networks in the last two to three decades aiding many problems in the domain of computer science, economics, physic...

    Authors: Anuj Singh, Rishi Ranjan Singh and S. R. S. Iyengar

    Citation: Computational Social Networks 2020 7:6

    Content type: Research

    Published on:

  12. The well-known minimum dominating set problem (MDSP) aims to construct the minimum-size subset of vertices in a graph such that every other vertex has at least one neighbor in the subset. In this article, we s...

    Authors: Minh Hai Nguyen, Minh Hoàng Hà, Diep N. Nguyen and The Trung Tran

    Citation: Computational Social Networks 2020 7:4

    Content type: Research

    Published on:

  13. Advising and mentoring Ph.D. students is an increasingly important aspect of the academic profession. We define and interpret a family of metrics (collectively referred to as “a-indices”) that can potentially be ...

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

    Citation: Computational Social Networks 2020 7:1

    Content type: Research

    Published on:

  14. We consider that a network of chaotic identical dynamical systems is connected to a new node. Depending on some properties of the network and on the way that connection is made, the new node may control the ne...

    Authors: Clara Grácio, Sara Fernandes and Luís Mário Lopes

    Citation: Computational Social Networks 2019 6:14

    Content type: Research

    Published on:

  15. The formation of robust communication networks between independently acting agents is of practical interest in multiple domains, for example, in sensor placement and Unmanned Aerial Vehicle communication. Thes...

    Authors: Christopher Diaz, Alexander Nikolaev, Abhinav Perla, Alexander Veremyev and Eduardo Pasiliao

    Citation: Computational Social Networks 2019 6:13

    Content type: Research

    Published on:

  16. Many systems are today modelled as complex networks, since this representation has been proven being an effective approach for understanding and controlling many real-world phenomena. A significant area of int...

    Authors: Vincenza Carchiolo, Marco Grassia, Alessandro Longheu, Michele Malgeri and Giuseppe Mangioni

    Citation: Computational Social Networks 2019 6:12

    Content type: Research

    Published on:

  17. Graphs naturally appear in numerous application domains, ranging from social analysis, bioinformatics to computer vision. The unique capability of graphs enables capturing the structural relations among data, ...

    Authors: Si Zhang, Hanghang Tong, Jiejun Xu and Ross Maciejewski

    Citation: Computational Social Networks 2019 6:11

    Content type: Research

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  18. Drug abuse continues to accelerate towards becoming the most severe public health problem in the United States. The ability to detect drug-abuse risk behavior at a population scale, such as among the populatio...

    Authors: Han Hu, NhatHai Phan, Soon A. Chun, James Geller, Huy Vo, Xinyue Ye, Ruoming Jin, Kele Ding, Deric Kenne and Dejing Dou

    Citation: Computational Social Networks 2019 6:10

    Content type: Research

    Published on:

  19. In the standard situation of networked populations, link neighbours represent one of the main influences leading to social diffusion of behaviour. When distinct attributes coexist, not only the network structu...

    Authors: Marie Lisa Kapeller, Georg Jäger and Manfred Füllsack

    Citation: Computational Social Networks 2019 6:9

    Content type: Research

    Published on:

  20. Prerequisite inadequacy causes more MOOC drop-out. As an effective method interfering with learning process, existing MOOC recommendation is mainly about subsequent learning objects that have not been learned ...

    Authors: Yanxia Pang, Na Wang, Ying Zhang, Yuanyuan Jin, Wendi Ji and Wenan Tan

    Citation: Computational Social Networks 2019 6:7

    Content type: Research

    Published on:

  21. In this paper, we address privacy issues related to ranked retrieval model in web databases, each of which takes private attributes as part of input in the ranking function. Many web databases keep private att...

    Authors: Tong Yan, Yunpeng Gao and Nan Zhang

    Citation: Computational Social Networks 2019 6:6

    Content type: Research

    Published on:

  22. In this paper, we develop a more general framework of block-structured Markov processes in the queueing study of blockchain systems, which can provide analysis both for the stationary performance measures and ...

    Authors: Quan-Lin Li, Jing-Yu Ma, Yan-Xia Chang, Fan-Qi Ma and Hai-Bo Yu

    Citation: Computational Social Networks 2019 6:5

    Content type: Research

    Published on:

  23. Unstructured data generated from sources such as the social media and traditional text documents are increasing and form a larger proportion of unanalysed data especially in the developing countries. In this s...

    Authors: Frank Namugera, Ronald Wesonga and Peter Jehopio

    Citation: Computational Social Networks 2019 6:3

    Content type: Research

    Published on:

  24. Economists and social scientists have studied the human migration extensively. However, the complex network of human mobility in the United States (US) is not studied in depth. In this paper, we analyze migrat...

    Authors: Batyr Charyyev and Mehmet Hadi Gunes

    Citation: Computational Social Networks 2019 6:1

    Content type: Research

    Published on:

  25. The paper is devoted to game-theoretic methods for community detection in networks. The traditional methods for detecting community structure are based on selecting dense subgraphs inside the network. Here we ...

    Authors: Konstantin E. Avrachenkov, Aleksei Y. Kondratev, Vladimir V. Mazalov and Dmytro G. Rubanov

    Citation: Computational Social Networks 2018 5:11

    Content type: Research

    Published on:

  26. Hashtags are widely used for communication in online media. As a condensed version of information, they characterize topics and discussions. For their analysis, we apply methods from network science and propos...

    Authors: Philipp Lorenz-Spreen, Frederik Wolf, Jonas Braun, Gourab Ghoshal, Nataša Djurdjevac Conrad and Philipp Hövel

    Citation: Computational Social Networks 2018 5:9

    Content type: Research

    Published on:

  27. Understanding traffic is an important challenge in different scientific fields. While there are many approaches to constructing traffic models, most of them rely on origin–destination data and have difficultie...

    Authors: Christian Hofer, Georg Jäger and Manfred Füllsack

    Citation: Computational Social Networks 2018 5:5

    Content type: Research

    Published on:

  28. In the framework of network sampling, random walk (RW) based estimation techniques provide many pragmatic solutions while uncovering the unknown network as little as possible. Despite several theoretical advan...

    Authors: Konstantin Avrachenkov, Vivek S. Borkar, Arun Kadavankandy and Jithin K. Sreedharan

    Citation: Computational Social Networks 2018 5:4

    Content type: Research

    Published on:

  29. Complex networks are found in many domains and the control of these networks is a research topic that continues to draw increasing attention. This paper proposes a method of network control that attempts to ma...

    Authors: Dave McKenney and Tony White

    Citation: Computational Social Networks 2018 5:3

    Content type: Research

    Published on:

  30. In this paper, we study the process of opinion dynamics and consensus building in online collaboration systems, in which users interact with each other following their common interests and their social profile...

    Authors: Ilire Hasani-Mavriqi, Dominik Kowald, Denis Helic and Elisabeth Lex

    Citation: Computational Social Networks 2018 5:2

    Content type: Research

    Published on:

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