IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v465y2017icp414-424.html
   My bibliography  Save this article

Optimizing transformations of structural balance in signed networks with potential relationships

Author

Listed:
  • Du, Haifeng
  • He, Xiaochen
  • Wang, Shanfeng
  • Gong, Maoguo
  • Feldman, Marcus W.

Abstract

A signed network includes positive edges, negative edges and “0” edges, the last of which denote potential relationships. However, “0” edges are commonly ignored in transformations of unbalanced networks. In this paper, we take “0” edges into account and solve the optimization problem in a more comprehensive way. We transform the unbalanced network by not only changing signs of edges but also changing edges into potential. The experimental results show that our method can solve this problem efficiently, and that our solutions are cost-saving.

Suggested Citation

  • Du, Haifeng & He, Xiaochen & Wang, Shanfeng & Gong, Maoguo & Feldman, Marcus W., 2017. "Optimizing transformations of structural balance in signed networks with potential relationships," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 414-424.
  • Handle: RePEc:eee:phsmap:v:465:y:2017:i:c:p:414-424
    DOI: 10.1016/j.physa.2016.08.027
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437116305441
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2016.08.027?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. repec:cup:cbooks:9780511771576 is not listed on IDEAS
    2. Sun, Yixiang & Du, Haifeng & Gong, Maoguo & Ma, Lijia & Wang, Shanfeng, 2014. "Fast computing global structural balance in signed networks based on memetic algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 261-272.
    3. Easley,David & Kleinberg,Jon, 2010. "Networks, Crowds, and Markets," Cambridge Books, Cambridge University Press, number 9780521195331.
    4. Figueiredo, Rosa & Frota, Yuri, 2014. "The maximum balanced subgraph of a signed graph: Applications and solution approaches," European Journal of Operational Research, Elsevier, vol. 236(2), pages 473-487.
    5. Michael Brusco & Douglas Steinley, 2011. "A Tabu-Search Heuristic for Deterministic Two-Mode Blockmodeling of Binary Network Matrices," Psychometrika, Springer;The Psychometric Society, vol. 76(4), pages 612-633, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lin, Geng & Guan, Jian & Feng, Huibin, 2018. "An ILP based memetic algorithm for finding minimum positive influence dominating sets in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 500(C), pages 199-209.
    2. Sheykhali, Somaye & Darooneh, Amir Hossein & Jafari, Gholam Reza, 2020. "Partial balance in social networks with stubborn links," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 548(C).
    3. Du, Haifeng & He, Xiaochen & Wang, Jingjing & Feldman, Marcus W., 2018. "Reversing structural balance in signed networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 780-792.
    4. Song, Shenpeng & Feng, Yuhao & Xu, Wenzhe & Li, Hui-Jia & Wang, Zhen, 2022. "Evolutionary prisoner’s dilemma game on signed networks based on structural balance theory," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Blazquez-Soriano, Amparo & Ramos-Sandoval, Rosmery, 2022. "Information transfer as a tool to improve the resilience of farmers against the effects of climate change: The case of the Peruvian National Agrarian Innovation System," Agricultural Systems, Elsevier, vol. 200(C).
    2. Martin L. Weitzman, 2015. "A Voting Architecture for the Governance of Free-Driver Externalities, with Application to Geoengineering," Scandinavian Journal of Economics, Wiley Blackwell, vol. 117(4), pages 1049-1068, October.
    3. Wei Zhong, 2017. "Simulating influenza pandemic dynamics with public risk communication and individual responsive behavior," Computational and Mathematical Organization Theory, Springer, vol. 23(4), pages 475-495, December.
    4. Guo Weilong & Minca Andreea & Wang Li, 2016. "The topology of overlapping portfolio networks," Statistics & Risk Modeling, De Gruyter, vol. 33(3-4), pages 139-155, December.
    5. Kobayashi, Teruyoshi & Takaguchi, Taro, 2018. "Identifying relationship lending in the interbank market: A network approach," Journal of Banking & Finance, Elsevier, vol. 97(C), pages 20-36.
    6. Konstantinos Antoniadis & Kostas Zafiropoulos & Vasiliki Vrana, 2016. "A Method for Assessing the Performance of e-Government Twitter Accounts," Future Internet, MDPI, vol. 8(2), pages 1-18, April.
    7. Maness, Michael & Cirillo, Cinzia, 2016. "An indirect latent informational conformity social influence choice model: Formulation and case study," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 75-101.
    8. Lomi, Alessandro & Fonti, Fabio, 2012. "Networks in markets and the propensity of companies to collaborate: An empirical test of three mechanisms," Economics Letters, Elsevier, vol. 114(2), pages 216-220.
    9. Zhang, Xuxi & Liu, Xianping & Lewis, Frank L. & Wang, Xia, 2020. "Bipartite tracking consensus of nonlinear multi-agent systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    10. Bing Han & Liyan Yang, 2013. "Social Networks, Information Acquisition, and Asset Prices," Management Science, INFORMS, vol. 59(6), pages 1444-1457, June.
    11. Dimitrios Karamanis, 2022. "Defence partnerships, military expenditure, investment, and economic growth: an analysis in PESCO countries," GreeSE – Hellenic Observatory Papers on Greece and Southeast Europe 173, Hellenic Observatory, LSE.
    12. Levent V. Orman, 2016. "Information markets over trust networks," Electronic Commerce Research, Springer, vol. 16(4), pages 529-551, December.
    13. Zhu, Yu-Xiao & Cao, Yan-Yan & Chen, Ting & Qiu, Xiao-Yan & Wang, Wei & Hou, Rui, 2018. "Crossover phenomena in growth pattern of social contagions with restricted contact," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 408-414.
    14. Pablo Galaso & Adrián Rodríguez Miranda & Sebastian Goinheix, 2018. "Local development, social capital and social network analysis: evidence from Uruguay," Revista de Estudios Regionales, Universidades Públicas de Andalucía, vol. 3, pages 137-163.
    15. Takahiro Ezaki & Naoki Masuda, 2017. "Reinforcement learning account of network reciprocity," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-8, December.
    16. Mariann Ollar & Marzena Rostek, 2011. "Information Aggregation and Innovation in Market Design," Working Papers 11-12, NET Institute.
    17. Mr. Jorge A Chan-Lau, 2017. "Variance Decomposition Networks: Potential Pitfalls and a Simple Solution," IMF Working Papers 2017/107, International Monetary Fund.
    18. Lillo, Felipe & Valdés, Rodrigo, 2016. "Dynamics of financial markets and transaction costs: A graph-based study," Research in International Business and Finance, Elsevier, vol. 38(C), pages 455-465.
    19. Usha Sridhar & Sridhar Mandyam, 2016. "Loan Allocation and Guarantee Structure for Group Borrower Networks in Microfinance," Studies in Microeconomics, , vol. 4(2), pages 100-114, December.
    20. Krawczyk, Malgorzata J. & Kułakowski, Krzysztof, 2022. "Structural balance in one time step," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:465:y:2017:i:c:p:414-424. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.