IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v415y2014icp261-272.html
   My bibliography  Save this article

Fast computing global structural balance in signed networks based on memetic algorithm

Author

Listed:
  • Sun, Yixiang
  • Du, Haifeng
  • Gong, Maoguo
  • Ma, Lijia
  • Wang, Shanfeng

Abstract

Structural balance is a large area of study in signed networks, and it is intrinsically a global property of the whole network. Computing global structural balance in signed networks, which has attracted some attention in recent years, is to measure how unbalanced a signed network is and it is a nondeterministic polynomial-time hard problem. Many approaches are developed to compute global balance. However, the results obtained by them are partial and unsatisfactory. In this study, the computation of global structural balance is solved as an optimization problem by using the Memetic Algorithm. The optimization algorithm, named Meme-SB, is proposed to optimize an evaluation function, energy function, which is used to compute a distance to exact balance. Our proposed algorithm combines Genetic Algorithm and a greedy strategy as the local search procedure. Experiments on social and biological networks show the excellent effectiveness and efficiency of the proposed method.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:phsmap:v:415:y:2014:i:c:p:261-272
    DOI: 10.1016/j.physa.2014.07.071
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437114006578
    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.2014.07.071?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:9780511761942 is not listed on IDEAS
    2. Galam, Serge, 1996. "Fragmentation versus stability in bimodal coalitions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 230(1), pages 174-188.
    3. Gong, Maoguo & Ma, Lijia & Zhang, Qingfu & Jiao, Licheng, 2012. "Community detection in networks by using multiobjective evolutionary algorithm with decomposition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(15), pages 4050-4060.
    4. Daolio, Fabio & Tomassini, Marco & Vérel, Sébastien & Ochoa, Gabriela, 2011. "Communities of minima in local optima networks of combinatorial spaces," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(9), pages 1684-1694.
    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. 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.
    2. 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.
    3. Wu, Yue & Gao, Lanlin & Zhang, Yi & Xiong, Xi, 2019. "Structural balance and dynamics over signed BA scale-free network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 866-877.
    4. 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.
    5. 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).
    6. Krawczyk, Malgorzata J. & Kułakowski, Krzysztof, 2022. "Structural balance in one time step," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    7. Peng Wu & Li Pan, 2015. "Multi-Objective Community Detection Based on Memetic Algorithm," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-31, May.

    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. Shang, Ronghua & Luo, Shuang & Zhang, Weitong & Stolkin, Rustam & Jiao, Licheng, 2016. "A multiobjective evolutionary algorithm to find community structures based on affinity propagation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 453(C), pages 203-227.
    2. Manuel Guerrero & Consolación Gil & Francisco G. Montoya & Alfredo Alcayde & Raúl Baños, 2020. "Multi-Objective Evolutionary Algorithms to Find Community Structures in Large Networks," Mathematics, MDPI, vol. 8(11), pages 1-18, November.
    3. Baldassarri, Simone & Gallo, Anna & Jacquier, Vanessa & Zocca, Alessandro, 2023. "Ising model on clustered networks: A model for opinion dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 623(C).
    4. Zou, Feng & Chen, Debao & Huang, De-Shuang & Lu, Renquan & Wang, Xude, 2019. "Inverse modelling-based multi-objective evolutionary algorithm with decomposition for community detection in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 662-674.
    5. Galam, Serge, 2004. "Sociophysics: a personal testimony," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 336(1), pages 49-55.
    6. Belaza, Andres M. & Ryckebusch, Jan & Bramson, Aaron & Casert, Corneel & Hoefman, Kevin & Schoors, Koen & van den Heuvel, Milan & Vandermarliere, Benjamin, 2019. "Social stability and extended social balance—Quantifying the role of inactive links in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 518(C), pages 270-284.
    7. Lu Wei & Na Liu & Junhua Chen & Jihong Sun, 2022. "Topic Evolution of Chinese COVID-19 Policies Based on Co-Occurrence Clustering Network Analysis," Sustainability, MDPI, vol. 14(4), pages 1-21, February.
    8. Shang, Ronghua & Liu, Huan & Jiao, Licheng, 2017. "Multi-objective clustering technique based on k-nodes update policy and similarity matrix for mining communities in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 1-24.
    9. Li, Jun-fang & Zhang, Bu-han & Liu, Yi-fang & Wang, Kui & Wu, Xiao-shan, 2012. "Spatial evolution character of multi-objective evolutionary algorithm based on self-organized criticality theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5490-5499.
    10. Wenxin Zhu & Huan Li & Wenhong Wei, 2023. "A Two-Stage Multi-Objective Evolutionary Algorithm for Community Detection in Complex Networks," Mathematics, MDPI, vol. 11(12), pages 1-13, June.
    11. Luis R. Izquierdo & Segismundo S. Izquierdo & José Manuel Galán & José Ignacio Santos, 2009. "Techniques to Understand Computer Simulations: Markov Chain Analysis," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(1), pages 1-6.
    12. Sebastian Herrmann & Gabriela Ochoa & Franz Rothlauf, 2016. "Communities of Local Optima as Funnels in Fitness Landscapes," Working Papers 1609, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    13. Tamás Vinkó & Kitti Gelle, 2017. "Basin Hopping Networks of continuous global optimization problems," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 25(4), pages 985-1006, December.
    14. Fu, Yu-Hsiang & Huang, Chung-Yuan & Sun, Chuen-Tsai, 2016. "Using a two-phase evolutionary framework to select multiple network spreaders based on community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 840-853.
    15. Shen, Yi, 2014. "The similarity of weights on edges and discovering of community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 560-570.
    16. Tomassini, Marco, 2021. "Complex networks analysis of the energy landscape of the low autocorrelation binary sequences problem," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 577(C).
    17. Karimi, Fatemeh & Lotfi, Shahriar & Izadkhah, Habib, 2021. "Community-guided link prediction in multiplex networks," Journal of Informetrics, Elsevier, vol. 15(4).
    18. Shang, Ronghua & Zhang, Weitong & Jiao, Licheng & Stolkin, Rustam & Xue, Yu, 2017. "A community integration strategy based on an improved modularity density increment for large-scale networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 471-485.
    19. Le Breton, Michel & Weber, Shlomo, 2009. "Existence of Pure Strategies Nash Equilibria in Social Interaction Games with Dyadic Externalities," CEPR Discussion Papers 7279, C.E.P.R. Discussion Papers.
    20. Ebrahimi, Morteza & Shahmoradi, Mohammad Reza & Heshmati, Zainabolhoda & Salehi, Mostafa, 2018. "A novel method for overlapping community detection using Multi-objective optimization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 825-835.

    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:415:y:2014:i:c:p:261-272. 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.