Abstract
Network evolution is one of the emerging research directions in the field of social network analysis, where link prediction plays a crucial role in modeling network dynamics in social networks. Link prediction has attracted a lot of attention of network engineers in developing several applications. In this paper, an effort has been made to model the network evolution through link prediction termed as LP-CD (Link prediction through community detection). We have leveraged the set of existing communities in the network for link prediction. Different community detection algorithms have been implemented to identify the dense subgroups in the network, which are further used in predicting future links. After identifying the dense subgroups in the network, the non-existing links inside the subgroups are identified using the global path-based similarity measures. The intuition of the proposed model is that two users are more likely to form a relationship in the future, if they belong to the same community and less likely to establish a relationship, if they belong to different communities. An extensive comparison of various existing models with LP-CD has been made by considering four real-world and three synthetic network datasets. The results show that the LP-CD outperforms other approaches for link prediction.
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References
Li R-H, Yu JX, Liu J (2011) Link prediction: the power of maximal entropy random walk. In: Proceedings of the 20th ACM international conference on Information and knowledge management. ACM, pp 1147–1156
Raj ED, Manogaran G, Srivastava G, Yulei W (2020) Information granulation-based community detection for social networks. IEEE Trans Comput Soc Syst 8(1):122–133
Cai T, Li J, Mian AS, Sellis T, Yu JX et al (2020) Target-aware holistic influence maximization in spatial social networks. IEEE Trans Knowl Data Eng 32(6):1–14
Naik D, Behera RK, Ramesh D, Rath SK (2020) Map-reduce-based centrality detection in social networks: an algorithmic approach. Arab J Sci Eng 45:10199–10222
Fan C, Jiang Y, Yang Y, Zhang C, Mostafavi A (2020) Crowd or hubs: information diffusion patterns in online social networks in disasters. Int J Disaster Risk Reduct 46:101498
Puig JS-C (2021) Contact recommendation in social networks: algorithmic models, diversity andÕ59 network evolution, A Ph. D thesis submitted to Compute Science Department, Autonomous University of Madrid, Madrid, Spain
Kumari A, Behera RK, Sahoo KS, Nayyar A, Luhach AK, Sahoo SP. Supervised link prediction using tructured-based feature extraction in social network. Concurrency and Computation: practice and Experience 32(3)1–16
Daud NN, Ab Hamid SH, Saadoon M, Sahran F, Anuar NB (2020) Applications of link prediction in social networks: a review. J Netw Comput Appl 166:102716
Behera RK, Naik D, Rath SK, Dharavath R (2020) Genetic algorithm-based community detection in large-scale social networks. Neural Comput Appl 32(13):9649–9665
Behera RK, Rath SK, Misra S, Damaševičius R, Maskeliūnas R (2017) Large scale community detection using a small world model. Appl Sci 7(11):1173
Borodin A, Filmus Y, Oren J (2010) Threshold models for competitive influence in social networks.Õ69 In: International workshop (WINE 2010): Internet and Network Economics Springer, pp 539–550
Liben-Nowell D, Kleinberg J (2007) The link-prediction problem for social networks. J Am Soc Inf Sci Technol 58(7):1019–1031
Soundarajan S, Hopcroft J (2012) Using community information to improve the precision of link prediction methods. In: Proceedings of the 21st international conference on world wide web. pp 607–608
Fani H, Jiang E, Bagheri E, Al-Obeidat F, Weichang D, Kargar M (2020) User community detection via embedding of social network structure and temporal content. Inf Process Manag 57(2):102056
Damasevicius R (2017). Recommendation based on review texts and social communities: a hybrid model, IEEE Access, 5(1):1–13
Shibata N, Kajikawa Y, Sakata I (2012) Link prediction in citation networks. J Am Soc Inf Sci Technol 63(1):78–85
Li F, He J, Huang G, Zhang Y, Yong S (2014) RETRACTED: A Clustering-based Link Prediction Method in Social Networks, Procedia Computer Science 29:432–442
Ozcan A, Oguducu SG (2019) Multivariate time series link prediction for evolving heterogeneous network. Int J Inf Technol Decis Mak 18(01):241–286
Li F, He J, Huang G, Zhang Y, Yong S (2014) A clustering-based link prediction method in social networks, Retracted
Shahriary SR, Shahriari M (2015) Noor RMD (2015) A community-based approach for link prediction in signed social networks. Sci Program
Zhou M (2015) Infinite edge partition models for overlapping community detection and link prediction. In: Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, PMLR 38: pp 1135–1143
Kong C, Li H, Zhang L, Zhu H, Liu T (2019) Link prediction on dynamic heterogeneous information networks. In: International conference on computational data and social networks. Springer, pp 339–350
Cheng H-M, Ning Y-Z, Yin Z, Yan C, Liu X, Zhang Z-Y (2018) Community detection in complex networks using link prediction. Mod Phys Lett B 32(01):1850004
Bastami E, Mahabadi A, Taghizadeh E (2019) A gravitation-based link prediction approach in social networks. Swarm Evolut Comput 44:176–186
Valverde-Rebaza J, de Andrade Lopes A (2012) Structural link prediction using community information on twitter. In: 2012 Fourth international conference on computational aspects of social networks (CASoN). IEEE, pp 132–137
De A, Bhattacharya S, Sarkar S, Ganguly N, Chakrabarti S (2016) Discriminative link prediction using local, community, and global signals. IEEE Trans Knowl Data Eng 28(8):2057–2070
De Bacco C, Power EA, Larremore DB, Moore C (2017) Community detection, link prediction, and layer interdependence in multilayer networks. Phys Rev E 95(4):042317
Behera RK, Sukla AS, Mahapatra S, Rath SK, Sahoo B, Bhattacharya S (2017) Map-reduce based link prediction for large scale social network, In: 29th International Conference on Software Engineering and Knowledge Engineering (SEKE 2017), IEEE, 1, pp 1–5
Liu W, Lü L (2010) Link prediction based on local random walk. EPL Europhys Lett 89(5):58007
Adamic LA, Adar E (2003) Friends and neighbors on the web. Soc Netw 25(3):211–230
Chen M, Liu J, Tang X (2008) Clustering via random walk hitting time on directed graphs. In: AAAI, vol 8. pp 616–621
Lusseau D, Schneider K, Boisseau OJ, Haase P, Slooten E, Dawson SM (2003) The bottlenose dolphin community of Doubtful Sound features a large proportion of long-lasting associations. Behav Ecol Sociobiol 54:396–405
Zachary WW (1977) An information flow model for conflict and fission in small groups. J Anthropol Res 33(4):452–473
McAuley, J. J., & Leskovec, J. (2012, December). Learning to discover social circles in ego networks. In In: Advances in neural information processing systems (NIPS) 2012:548–556
Klimt B, Yang Y (2004) The enron corpus: a new dataset for email classification research. In: European conference on machine learning. Springer, pp 217–226
Lancichinetti A, Fortunato S, Radicchi F (2008) Benchmark graphs for testing community detection algorithms. Phys Rev E 78(4):046110
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Kumari, A., Behera, R.K., Sahoo, B. et al. Prediction of link evolution using community detection in social network. Computing 104, 1077–1098 (2022). https://doi.org/10.1007/s00607-021-01035-4
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DOI: https://doi.org/10.1007/s00607-021-01035-4