Identifying influential spreaders using multi-objective artificial bee colony optimization

Abstract Advertisement over social networks is critical for many businesses, and selecting the initial set of influential nodes for which the advertising message is passed, is regarded as an important issue in this regard. Although various measures have been proposed for specifying the influentiality of a set, it is affected by different factors. In this paper, a multi-objective function is first defined as an influentiality measure, and finding such an initial is framed as an optimization problem. Then, using artificial bee colony optimization two approaches are proposed to solve the problem. In the first approach, influentiality of nodes is only taken into account, while in the second method a budget constraint is also considered. Different experiments on real networks are conducted to evaluate the proposed methods, where the obtained results show their outperformance over state-of-the-art influence maximization methods.

[1]  Jianguo Liu,et al.  Identifying multiple influential spreaders in term of the distance-based coloring , 2016 .

[2]  A. Fatemi,et al.  Influential nodes ranking in complex networks: An entropy-based approach , 2017 .

[3]  Fuzhen Zhuang,et al.  Balanced Seed Selection for Budgeted Influence Maximization in Social Networks , 2014, PAKDD.

[4]  Dervis Karaboga,et al.  A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm , 2007, J. Glob. Optim..

[5]  Carlos A. Coello Coello,et al.  Handling multiple objectives with particle swarm optimization , 2004, IEEE Transactions on Evolutionary Computation.

[6]  Dongyun Yi,et al.  Effective identification of multiple influential spreaders by DegreePunishment , 2016 .

[7]  Tiranee Achalakul,et al.  The best-so-far selection in Artificial Bee Colony algorithm , 2011, Appl. Soft Comput..

[8]  Dilip Kumar Pratihar,et al.  ComBIM: A community-based solution approach for the Budgeted Influence Maximization Problem , 2019, Expert Syst. Appl..

[9]  Lev Muchnik,et al.  Identifying influential spreaders in complex networks , 2010, 1001.5285.

[10]  Reza Akbari,et al.  A multi-objective artificial bee colony algorithm , 2012, Swarm Evol. Comput..

[11]  Mahdi Jalili,et al.  Identification of influential users in social networks based on users' interest , 2019, Inf. Sci..

[12]  Mohammad Ali Nematbakhsh,et al.  IMPROVING DETECTION OF INFLUENTIAL NODES IN COMPLEX NETWORKS , 2015, ArXiv.

[13]  Kalyanmoy Deb,et al.  A Fast Elitist Non-dominated Sorting Genetic Algorithm for Multi-objective Optimisation: NSGA-II , 2000, PPSN.

[14]  Ponnuthurai N. Suganthan,et al.  Multi-objective evolutionary programming without non-domination sorting is up to twenty times faster , 2009, 2009 IEEE Congress on Evolutionary Computation.

[15]  Yuren Zhou,et al.  An elitism based multi-objective artificial bee colony algorithm , 2015, Eur. J. Oper. Res..

[16]  Keyhan Khamforoosh,et al.  Influence maximization in social networks based on TOPSIS , 2018, Expert Syst. Appl..

[17]  Andreas Krause,et al.  Cost-effective outbreak detection in networks , 2007, KDD '07.

[18]  L. Freeman.  Centrality in social networks conceptual clarification , 1978 .

[19]  Matjaz Perc,et al.  Information cascades in complex networks , 2017, J. Complex Networks.

[20]  Jay Prakash,et al.  NSABC: Non-dominated sorting based multi-objective artificial bee colony algorithm and its application in data clustering , 2016, Neurocomputing.

[21]  Wei Chen,et al.  Efficient influence maximization in social networks , 2009, KDD.

[22]  Gert Sabidussi,et al.  The centrality index of a graph , 1966 .

[23]  Mehmet Çunkas,et al.  Color image segmentation based on multiobjective artificial bee colony optimization , 2015, Appl. Soft Comput..

[24]  Ahmad Zareie,et al.  EHC: Extended H-index Centrality measure for identification of users’ spreading influence in complex networks , 2019, Physica A: Statistical Mechanics and its Applications.

[25]  Mohammad Ali Nematbakhsh,et al.  Identification of multi-spreader users in social networks for viral marketing , 2017, J. Inf. Sci..

[26]  Ahmad Zareie,et al.  A hierarchical approach for influential node ranking in complex social networks , 2018, Expert Syst. Appl..

[27]  Hanning Chen,et al.  Solving Multiobjective Optimization Problems Using Artificial Bee Colony Algorithm , 2011 .

[28]  Mohammad Ali Nematbakhsh,et al.  Identification of influential users by neighbors in online social networks , 2017 .

[29]  Wei Chen,et al.  Scalable influence maximization for prevalent viral marketing in large-scale social networks , 2010, KDD.

[30]  Haifeng Zhang,et al.  Identifying multiple influential spreaders by a heuristic clustering algorithm , 2017 .

[31]  Mahdi Jalili,et al.  Influential node ranking in social networks based on neighborhood diversity , 2019, Future Gener. Comput. Syst..

[32]  Ya Zhao,et al.  Fast ranking influential nodes in complex networks using a k-shell iteration factor , 2016 .

[33]  Zhuo-Ming Ren,et al.  Effects of the distance among multiple spreaders on the spreading , 2014 .

[34]  M. N. Amar,et al.  Application of hybrid support vector regression artificial bee colony for prediction of MMP in CO2-EOR process , 2018 .

[35]  Lothar Thiele,et al.  Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach , 1999, IEEE Trans. Evol. Comput..

[36]  Yunjun Gao,et al.  Group-Level Influence Maximization with Budget Constraint , 2017, DASFAA.

[37]  Hui Gao,et al.  Identifying Influential Nodes in Large-Scale Directed Networks: The Role of Clustering , 2013, PloS one.

[38]  Éva Tardos,et al.  Maximizing the Spread of Influence through a Social Network , 2015, Theory Comput..

[39]  Rong Zheng,et al.  On Budgeted Influence Maximization in Social Networks , 2012, IEEE Journal on Selected Areas in Communications.

[40]  Leonard M. Freeman,et al.  A set of measures of centrality based upon betweenness , 1977 .

[41]  Ching-Lai Hwang,et al.  Methods for Multiple Attribute Decision Making , 1981 .