[1] M. Granovetter, "Network sampling: Some first steps," American journal of sociology, vol. 81, no. 6, pp. 1287-1303, 1976.
[2] L. A. Sanchis, "Multiple-way network partitioning," IEEE Transactions on Computers, vol. 38, no. 1, pp. 62-81, 1989.
[3] V. Chandola, A. Banerjee, and V. Kumar, "Anomaly detection: A survey," ACM computing surveys (CSUR), vol. 41, no. 3, pp. 1-58, 2009.
[4] J. Yang and J. Liu, "Influence maximization-cost minimization in social networks based on a multiobjective discrete particle swarm optimization algorithm," IEEE Access, vol. 6, pp. 2320-2329, 2017.
[5] K. Deb, A. Pratap, S. Agarwal, T. Meyarivan, and A. Fast, "Nsga-ii," IEEE transactions on evolutionary computation, vol. 6, no. 2, pp. 182-197, 2002.
[6] M. Richardson and P. Domingos, "Mining knowledge-sharing sites for viral marketing," in Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining, 2002, pp. 61-70.
[7] P. Domingos and M. Richardson, "Mining the network value of customers," in Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining, 2001, pp. 57-66.
[8] D. Kempe, J. Kleinberg, and É. Tardos, "Maximizing the spread of influence through a social network," in Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining, 2003, pp. 137-146.
[9] D. Kempe, J. Kleinberg, and É. Tardos, "Influential nodes in a diffusion model for social networks," in Automata, Languages and Programming: 32nd International Colloquium, ICALP 2005, Lisbon, Portugal, July 11-15, 2005. Proceedings 32, 2005: Springer, pp. 1127-1138.
[10] J. Leskovec, A. Krause, C. Guestrin, C. Faloutsos, J. VanBriesen, and N. Glance, "Cost-effective outbreak detection in networks," in Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining, 2007, pp. 420-429.
[11] A. Goyal, W. Lu, and L. V. Lakshmanan, "Celf++ optimizing the greedy algorithm for influence maximization in social networks," in Proceedings of the 20th international conference companion on World wide web, 2011, pp. 47-48.
[12] Y. Tang, X. Xiao, and Y. Shi, "Influence maximization: Near-optimal time complexity meets practical efficiency," in Proceedings of the 2014 ACM SIGMOD international conference on Management of data, 2014, pp. 75-86.
[13] H. T. Nguyen, M. T. Thai, and T. N. Dinh, "A billion-scale approximation algorithm for maximizing benefit in viral marketing," IEEE/ACM Transactions On Networking, vol. 25, no. 4, pp. 2419-2429, 2017.
[14] C. Borgs, M. Brautbar, J. Chayes, and B. Lucier, "Maximizing social influence in nearly optimal time," in Proceedings of the twenty-fifth annual ACM-SIAM symposium on Discrete algorithms, 2014: SIAM, pp. 946-957.
[15] J. Lv, J. Guo, and H. Ren, "Efficient greedy algorithms for influence maximization in social networks," Journal of Information Processing Systems, vol. 10, no. 3, pp. 471-482, 2014.
[16] L. C. Freeman, "Centrality in social networks: Conceptual clarification," Social network: critical concepts in sociology. Londres: Routledge, vol. 1, pp. 238-263, 2002.
[17] W. Chen, Y. Wang, and S. Yang, "Efficient influence maximization in social networks," in Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, 2009, pp. 199-208.
[18] K. Jung, W. Heo, and W. Chen, "Irie: Scalable and robust influence maximization in social networks," in 2012 IEEE 12th international conference on data mining, 2012: IEEE, pp. 918-923.
[19] D. Bucur and G. Iacca, "Influence maximization in social networks with genetic algorithms," in Applications of Evolutionary Computation: 19th European Conference, EvoApplications 2016, Porto, Portugal, March 30--April 1, 2016, Proceedings, Part I 19, 2016: Springer, pp. 379-392.
[20] P. Krömer and J. Nowaková, "Guided genetic algorithm for the influence maximization problem," in Computing and Combinatorics: 23rd International Conference, COCOON 2017, Hong Kong, China, August 3-5, 2017, Proceedings 23, 2017: Springer, pp. 630-641.
[21] C.-W. Tsai, Y.-C. Yang, and M.-C. Chiang, "A genetic newgreedy algorithm for influence maximization in social network," in 2015 IEEE International Conference on Systems, Man, and Cybernetics, 2015: IEEE, pp. 2549-2554.
[22] D. Bucur, G. Iacca, A. Marcelli, G. Squillero, and A. Tonda, "Multi-objective evolutionary algorithms for influence maximization in social networks," in Applications of Evolutionary Computation: 20th European Conference, EvoApplications 2017, Amsterdam, The Netherlands, April 19-21, 2017, Proceedings, Part I 20, 2017: Springer, pp. 221-233.
[23] J.-b. Guo, F.-z. Chen, and M.-q. Li, "A multi-objective optimization approach for influence maximization in social networks," in Proceeding of the 24th International Conference on Industrial Engineering and Engineering Management 2018, 2019: Springer, pp. 706-715.
[24] P.-L. Lu, L. Zhang, J.-X. Tang, J.-M. Lan, H.-Y. Zhu, and S.-H. Song, "Solving the Influence Maximization-Cost Minimization Problem in Social Networks by Using a Multi-Objective Differential Evolution Algorithm," Journal of Computers, vol. 34, no. 5, pp. 285-303, 2023.
[25] P. Wang and R. Zhang, "A multi-objective crow search algorithm for influence maximization in social networks," Electronics, vol. 12, no. 8, p. 1790, 2023.
[26] L. Zhang, Y. Liu, F. Cheng, J. Qiu, and X. Zhang, "A local-global influence indicator based constrained evolutionary algorithm for budgeted influence maximization in social networks," IEEE Transactions on Network Science and Engineering, vol. 8, no. 2, pp. 1557-1570, 2021.
[27] J. Yang and J. Liu, "Influence Maximization-Cost Minimization in Social Networks Based on a Multiobjective Discrete Particle Swarm Optimization Algorithm," IEEE Access, vol. 6, pp. 2320-2329, 2018, doi: 10.1109/ACCESS.2017.2782814.
[28] S. Genetti, E. Ribaga, E. Cunegatti, Q. F. Lotito, and G. Iacca, "Influence Maximization in Hypergraphs using Multi-Objective Evolutionary Algorithms," arXiv preprint arXiv:2405.10187, 2024.
[29] X. Fu, R. R. Bhatt, S. Basu, and A. Pavan, "Multi-objective submodular optimization with approximate oracles and influence maximization," in 2021 IEEE International Conference on Big Data (Big Data), 2021: IEEE, pp. 328-334.