[1] Y. Li, J. Fan, Y. Wang, and K.-L. L. Tan, “Influence Maximization on Social Graphs: A Survey,” IEEE Trans. Knowl. Data Eng., vol. 30, no. 10, pp. 1852–1872, Oct. 2018.
[2] K. Li, L. Zhang, and H. Huang, “Social Influence Analysis: Models, Methods, and Evaluation,” Engineering, vol. 4, no. 1, pp. 40–46, Feb. 2018.
[3] 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.
[4] D. Kempe, J. Kleinberg, and É. Tardos, “Maximizing the spread of influence through a social network,” in Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2003, pp. 137–146.
[5] J. Leskovec, A. Krause, C. Guestrin, C. Faloutsos, J. Vanbriesen, and N. Glance, “Cost-effective outbreak detection in networks,” in Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2007, pp. 420–429.
[6] A. Goyal, W. Lu, and L. V. S. Lakshmanan, “CELF++: Optimizing the greedy algorithm for influence maximization in social networks,” in Proceedings of the 20th International Conference Companion on World Wide Web, WWW 2011, 2011, pp. 47–48.
[7] W. Chen, Y. Wang, and S. Yang, “Efficient influence maximization in social networks,” in Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2009, pp. 199–207.
[8] S. Cheng, H. Shen, J. Huang, G. Zhang, and X. Cheng, “StaticGreedy: Solving the scalability-accuracy dilemma in influence maximization,” in International Conference on Information and Knowledge Management, Proceedings, 2013, pp. 509–518.
[9] C. Zhou, P. Zhang, W. Zang, and L. Guo, “On the Upper Bounds of Spread for Greedy Algorithms in Social Network Influence Maximization,” IEEE Trans. Knowl. Data Eng., vol. 27, no. 10, pp. 2770–2783, Oct. 2015.
[10] Y. Tang, X. Xiao, and Y. Shi, “Influence maximization: Near-optimal time complexity meets practical efficiency,” in Proceedings of the ACM SIGMOD International Conference on Management of Data, 2014, pp. 75–86.
[11] Y. Tang, Y. Shi, and X. Xiao, “Influence maximization in near-linear time: A martingale approach,” in Proceedings of the ACM SIGMOD International Conference on Management of Data, 2015, vol. 2015-May, pp. 1539–1554.
[12] S. Banerjee, M. Jenamani, and D. K. Pratihar, “A survey on influence maximization in a social network,” Knowl. Inf. Syst., vol. 62, no. 9, pp. 3417–3455, Sep. 2020.
[13] S. Peng, Y. Zhou, L. Cao, S. Yu, J. Niu, and W. Jia, “Influence analysis in social networks: A survey,” J. Netw. Comput. Appl., vol. 106, pp. 17–32, Mar. 2018.
[14] L. Page, L. Page, S. Brin, R. Motwani, and T. Winograd, “The PageRank Citation Ranking: Bringing Order to the Web,” -, 1998.
[15] J. M. Kleinberg, “Authoritative sources in a hyperlinked environment,” J. ACM, vol. 46, no. 5, pp. 604–632, 1999.
[16] A. Goyal, W. Lu, and L. V. S. Lakshmanan, “SIMPATH: An Efficient Algorithm for Influence Maximization under the Linear Threshold Model,” in 2011 IEEE 11th International Conference on Data Mining, 2011, pp. 211–220.
[17] M. Kimura, K. Saito, R. Nakano, and H. Motoda, “Extracting influential nodes on a social network for information diffusion,” Data Min. Knowl. Discov., vol. 20, no. 1, pp. 70–97, Jan. 2010.
[18] W. Chen, C. Wang, and Y. Wang, “Scalable influence maximization for prevalent viral marketing in large-scale social networks,” in Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010, pp. 1029–1038.
[19] J. Kim, S. K. Kim, and H. Yu, “Scalable and parallelizable processing of influence maximization for large-scale social networks?,” in Proceedings - International Conference on Data Engineering, 2013, pp. 266–277.
[20] W. Chen, Y. Yuan, and L. Zhang, “Scalable influence maximization in social networks under the linear threshold model,” in Proceedings - IEEE International Conference on Data Mining, ICDM, 2010, pp. 88–97.
[21] R. Narayanam and Y. Narahari, “A shapley value-based approach to discover influential nodes in social networks,” IEEE Trans. Autom. Sci. Eng., vol. 8, no. 1, pp. 130–147, Jan. 2011.
[22] K. Jung, W. Heo, and W. Chen, “IRIE: Scalable and robust influence maximization in social networks,” in Proceedings - IEEE International Conference on Data Mining, ICDM, 2012, pp. 918–923.
[23] Q. Liu, B. Xiang, E. Chen, H. Xiong, F. Tang, and J. X. Yu, “Influence maximization over large-scale social networks: A bounded linear approach,” in CIKM 2014 - Proceedings of the 2014 ACM International Conference on Information and Knowledge Management, 2014, pp. 171–180.
[24] S. Cheng, H.-W. Shen, J. Huang, W. Chen, and X.-Q. Cheng, “IMRank: Influence Maximization via Finding Self-Consistent Ranking,” SIGIR 2014 - Proc. 37th Int. ACM SIGIR Conf. Res. Dev. Inf. Retr., pp. 475–484, Feb. 2014.
[25] N. Ohsaka, T. Akiba, Y. Yoshida, and K. Kawarabayashi, “Fast and accurate influence maximization on large networks with pruned Monte-Carlo simulations,” in Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014, pp. 138–144.
[26] S. Galhotra, A. Arora, and S. Roy, “Holistic Influence Maximization: Combining Scalability and Efficiency with Opinion-Aware Models,” Proc. ACM SIGMOD Int. Conf. Manag. Data, vol. 26-June-20, pp. 743–758, Feb. 2016.
[27] N. Sumith, B. Annappa, and S. Bhattacharya, “Influence maximization in large social networks: Heuristics, models and parameters,” Futur. Gener. Comput. Syst., vol. 89, pp. 777–790, Dec. 2018.
[28] M. Zarezade, E. Nourani, and A. Bouyer, “Community Detection using a New Node Scoring and Synchronous Label Updating of Boundary Nodes in Social Networks,” J. AI Data Min., vol. 8, no. 2, pp. 201–212, 2020.
[29] Y. Wang, G. Cong, G. Song, and K. Xie, “Community-based Greedy Algorithm for Mining top-K Influential Nodes in Mobile Social Networks,” in Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010, pp. 1039–1048.
[30] H. Li, S. S. Bhowmick, A. Sun, and J. Cui, “Conformity-aware influence maximization in online social networks,” VLDB J., vol. 24, no. 1, pp. 117–141, Jan. 2015.
[31] A. Bozorgi, H. Haghighi, M. Sadegh Zahedi, and M. Rezvani, “INCIM: A community-based algorithm for influence maximization problem under the linear threshold model,” Inf. Process. Manag., vol. 52, no. 6, pp. 1188–1199, Nov. 2016.
[32] Y. Y. Ko, K. J. Cho, and S. W. Kim, “Efficient and effective influence maximization in social networks: A hybrid-approach,” Inf. Sci. (Ny)., vol. 465, pp. 144–161, Oct. 2018.
[33] J. Shang, H. Wu, S. Zhou, J. Zhong, Y. Feng, and B. Qiang, “IMPC: Influence maximization based on multi-neighbor potential in community networks,” Phys. A Stat. Mech. its Appl., vol. 512, pp. 1085–1103, Dec. 2018.
[34] S. Jendoubi, A. Martin, L. Liétard, H. Ben Hadji, and B. Ben Yaghlane, “Two evidential data based models for influence maximization in Twitter,” Knowledge-Based Syst., vol. 121, pp. 58–70, Apr. 2017.
[35] G. Corneuejols, M. L. Fisher, and G. L. Nemhauser, “Location of Bank Accounts to Optimize Float: An Analytic Study of Exact and Approximate Algorithms.,” Manage. Sci., vol. 23, no. 8, pp. 789–810, Apr. 1977.
[36] G. L. Nemhauser, L. A. Wolsey, and M. L. Fisher, “An analysis of approximations for maximizing submodular set functions-I,” Math. Program., vol. 14, no. 1, pp. 265–294, Dec. 1978.
[37] R. A. Rossi and N. K. Ahmed, “The Network Data Repository with Interactive Graph Analytics and Visualization,” in AAAI, 2015. [Online]. Available: https://networkrepository.com/. [Accessed: 25-Oct-2020].
[38] J. Leskovec and A. Krevl, “SNAP Datasets,” Stanford, Jun-2014. [Online]. Available: http://snap.stanford.edu/data. [Accessed: 25-Oct-2020].