IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v392y2013i5p1215-1231.html
   My bibliography  Save this article

Community detection based on modularity and an improved genetic algorithm

Author

Listed:
  • Shang, Ronghua
  • Bai, Jing
  • Jiao, Licheng
  • Jin, Chao

Abstract

Complex networks are widely applied in every aspect of human society, and community detection is a research hotspot in complex networks. Many algorithms use modularity as the objective function, which can simplify the algorithm. In this paper, a community detection method based on modularity and an improved genetic algorithm (MIGA) is put forward. MIGA takes the modularity Q as the objective function, which can simplify the algorithm, and uses prior information (the number of community structures), which makes the algorithm more targeted and improves the stability and accuracy of community detection. Meanwhile, MIGA takes the simulated annealing method as the local search method, which can improve the ability of local search by adjusting the parameters. Compared with the state-of-art algorithms, simulation results on computer-generated and four real-world networks reflect the effectiveness of MIGA.

Suggested Citation

  • Shang, Ronghua & Bai, Jing & Jiao, Licheng & Jin, Chao, 2013. "Community detection based on modularity and an improved genetic algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(5), pages 1215-1231.
    • Handle: RePEc:eee:phsmap:v:392:y:2013:i:5:p:1215-1231
    DOI: 10.1016/j.physa.2012.11.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437112009673
    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.2012.11.003?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. Gergely Palla & Imre Derényi & Illés Farkas & Tamás Vicsek, 2005. "Uncovering the overlapping community structure of complex networks in nature and society," Nature, Nature, vol. 435(7043), pages 814-818, June.
    2. Stoico, César O. & Renzi, Danilo G. & Vericat, Fernando, 2008. "A genetic algorithm for the 1D electron gas," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(1), pages 159-166.
    3. Xie, Fuding & Ji, Min & Zhang, Yong & Huang, Dan, 2009. "The detection of community structure in network via an improved spectral method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(15), pages 3268-3272.
    4. Wu, Zhihao & Lin, Youfang & Wan, Huaiyu & Tian, Shengfeng & Hu, Keyun, 2012. "Efficient overlapping community detection in huge real-world networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(7), pages 2475-2490.
    5. Faqeeh, Ali & Aghababaei Samani, Keivan, 2012. "Community detection based on the “clumpiness” matrix in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(7), pages 2463-2474.
    6. Jiang, Jonathan Q. & McQuay, Lisa J., 2012. "Modularity functions maximization with nonnegative relaxation facilitates community detection in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(3), pages 854-865.
    7. Wang, Xiaohua & Jiao, Licheng & Wu, Jianshe, 2009. "Adjusting from disjoint to overlapping community detection of complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(24), pages 5045-5056.
    8. Zhang, Dawei & Xie, Fuding & Zhang, Yong & Dong, Fangyan & Hirota, Kaoru, 2010. "Fuzzy analysis of community detection in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(22), pages 5319-5327.
    9. Pan, Ying & Li, De-Hua & Liu, Jian-Guo & Liang, Jing-Zhang, 2010. "Detecting community structure in complex networks via node similarity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(14), pages 2849-2857.
    10. Wu, Jianshe & Wang, Xiaohua & Jiao, Licheng, 2012. "Synchronization on overlapping community network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(3), pages 508-514.
    11. Wu, Jieyu & Shao, Xinyu & Li, Jinhang & Huang, Gang, 2012. "Scale-free properties of information flux networks in genetic algorithms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1692-1701.
    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. Saoud, Bilal & Moussaoui, Abdelouahab, 2018. "A new hierarchical method to find community structure in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 495(C), pages 418-426.
    2. 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.
    3. Bilal, Saoud & Abdelouahab, Moussaoui, 2017. "Evolutionary algorithm and modularity for detecting communities in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 89-96.
    4. Li, Yafang & Jia, Caiyan & Yu, Jian, 2015. "A parameter-free community detection method based on centrality and dispersion of nodes in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 321-334.
    5. Moradi, Mehdi & Parsa, Saeed, 2019. "An evolutionary method for community detection using a novel local search strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 457-475.
    6. Li, Yafang & Jia, Caiyan & Li, Jianqiang & Wang, Xiaoyang & Yu, Jian, 2018. "Enhanced semi-supervised community detection with active node and link selection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 219-232.
    7. Guobin Chen & Tangsen Huang, 2019. "Community privacy estimation method based on key node method in space social Internet of Things," International Journal of Distributed Sensor Networks, , vol. 15(10), pages 15501477198, October.
    8. Chen, Kaiqi & Bi, Weihong, 2019. "A new genetic algorithm for community detection using matrix representation method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    9. Li, Shudong & Jiang, Laiyuan & Wu, Xiaobo & Han, Weihong & Zhao, Dawei & Wang, Zhen, 2021. "A weighted network community detection algorithm based on deep learning," Applied Mathematics and Computation, Elsevier, vol. 401(C).
    10. Dhuha Abdulhadi Abduljabbar & Siti Zaiton Mohd Hashim & Roselina Sallehuddin, 2020. "Nature-inspired optimization algorithms for community detection in complex networks: a review and future trends," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 74(2), pages 225-252, June.
    11. Zhao, Danling & Li, Jichao & Tan, Yuejin & Yang, Kewei & Ge, Bingfeng & Dou, Yajie, 2018. "Optimization adjustment of human resources based on dynamic heterogeneous network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 45-57.
    12. Li, Wei & Huang, Ce & Wang, Miao & Chen, Xi, 2017. "Stepping community detection algorithm based on label propagation and similarity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 472(C), pages 145-155.
    13. 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.
    14. Cai, Biao & Wang, Yanpeng & Zeng, Lina & Hu, Yanmei & Li, Hongjun, 2020. "Edge classification based on Convolutional Neural Networks for community detection in complex network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
    15. 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.
    16. 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.
    17. Shang, Ronghua & Luo, Shuang & Li, Yangyang & Jiao, Licheng & Stolkin, Rustam, 2015. "Large-scale community detection based on node membership grade and sub-communities integration," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 279-294.
    18. Leila M Naeni & Hugh Craig & Regina Berretta & Pablo Moscato, 2016. "A Novel Clustering Methodology Based on Modularity Optimisation for Detecting Authorship Affinities in Shakespearean Era Plays," PLOS ONE, Public Library of Science, vol. 11(8), pages 1-27, August.

    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. Wu, Jianshe & Lu, Rui & Jiao, Licheng & Liu, Fang & Yu, Xin & Wang, Da & Sun, Bo, 2013. "Phase transition model for community detection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1287-1301.
    3. 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.
    4. 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.
    5. Mu, Caihong & Liu, Yong & Liu, Yi & Wu, Jianshe & Jiao, Licheng, 2014. "Two-stage algorithm using influence coefficient for detecting the hierarchical, non-overlapping and overlapping community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 408(C), pages 47-61.
    6. Sun, Hong-liang & Ch’ng, Eugene & Yong, Xi & Garibaldi, Jonathan M. & See, Simon & Chen, Duan-bing, 2018. "A fast community detection method in bipartite networks by distance dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 108-120.
    7. Yang, Kai & Guo, Qiang & Liu, Jian-Guo, 2018. "Community detection via measuring the strength between nodes for dynamic networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 256-264.
    8. Liu, Xu & Forrest, Jeffrey Yi-Lin & Luo, Qiang & Yi, Dong-Yun, 2012. "Detecting community structure using biased random merging," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1797-1810.
    9. Ji, Junzhong & Song, Xiangjing & Liu, Chunnian & Zhang, Xiuzhen, 2013. "Ant colony clustering with fitness perception and pheromone diffusion for community detection in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(15), pages 3260-3272.
    10. Shang, Ronghua & Luo, Shuang & Li, Yangyang & Jiao, Licheng & Stolkin, Rustam, 2015. "Large-scale community detection based on node membership grade and sub-communities integration," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 279-294.
    11. Jorge Peña & Yannick Rochat, 2012. "Bipartite Graphs as Models of Population Structures in Evolutionary Multiplayer Games," PLOS ONE, Public Library of Science, vol. 7(9), pages 1-13, September.
    12. Chen, Ling-Jiao & Zhang, Zi-Ke & Liu, Jin-Hu & Gao, Jian & Zhou, Tao, 2017. "A vertex similarity index for better personalized recommendation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 607-615.
    13. Shang, Jiaxing & Liu, Lianchen & Li, Xin & Xie, Feng & Wu, Cheng, 2016. "Targeted revision: A learning-based approach for incremental community detection in dynamic networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 70-85.
    14. Ying Song & Zhiwen Zheng & Yunmei Shi & Bo Wang, 2023. "GLOD: The Local Greedy Expansion Method for Overlapping Community Detection in Dynamic Provenance Networks," Mathematics, MDPI, vol. 11(15), pages 1-16, July.
    15. Zhang, Zhiwei & Wang, Zhenyu, 2015. "Mining overlapping and hierarchical communities in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 25-33.
    16. Masa Tsuchiya & Vincent Piras & Alessandro Giuliani & Masaru Tomita & Kumar Selvarajoo, 2010. "Collective Dynamics of Specific Gene Ensembles Crucial for Neutrophil Differentiation: The Existence of Genome Vehicles Revealed," PLOS ONE, Public Library of Science, vol. 5(8), pages 1-10, August.
    17. Wu, Zhihao & Lin, Youfang & Wan, Huaiyu & Tian, Shengfeng & Hu, Keyun, 2012. "Efficient overlapping community detection in huge real-world networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(7), pages 2475-2490.
    18. Nie, Yanyi & Li, Wenyao & Pan, Liming & Lin, Tao & Wang, Wei, 2022. "Markovian approach to tackle competing pathogens in simplicial complex," Applied Mathematics and Computation, Elsevier, vol. 417(C).
    19. Rizman Žalik, Krista & Žalik, Borut, 2014. "A local multiresolution algorithm for detecting communities of unbalanced structures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 407(C), pages 380-393.
    20. Zhang, Shihua & Wang, Rui-Sheng & Zhang, Xiang-Sun, 2007. "Identification of overlapping community structure in complex networks using fuzzy c-means clustering," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 374(1), pages 483-490.

    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:392:y:2013:i:5:p:1215-1231. 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.