An agent-based modeling approach for the influence maximization problem

Identifying first users (target set) of a new product entering a market is critical in forecasting the market share, but also it is a hard-to-solve problem. In this paper, we develop an agent-based modeling approach as a simulation method. We study characteristic features of the target set, such as their importance over the social network and persuasion skills, together with the size of the set and the new product adoption of the rest of the network, to understand their effects on product spread. We evaluate solutions of 12 scenarios with numerical experiments based on these characteristics.Pazara yeni girecek bir ürünün öncelikli olarak kullanımına sunulacağı kişilerin (hedef kümenin) belirlenmesi pazar payı tahmini yapmak için önemli, ancak çözülmesi zor bir problemdir. Bu makalede, bu problem için ajan-bazlı modelleme ile bir simülasyon çalışması geliştirilmiştir. Hedef kümeye seçilmiş kişilerin sosyal ağ üzerindeki önemi, ikna becerileri, diğerlerinin yeni ürün adaptasyonu gibi karakteristik özelliklerin ve hedef küme büyüklüğünün ürünün yayılması üzerindeki etkileri incelenmektedir. Bu özelliklere bağlı 12 farklı senaryo için çözümler değerlendirilmiştir

On the optimal solution of budgeted influence maximization problem in social networks

The budgeted influence maximization problem is a challenging stochastic optimization problem defined on social networks. In this problem, the objective is identifying influential individuals who can influence the maximum number of members within a limited budget. In this work an integer program that approximates the original problem is developed and solved by a sample average approximation (SAA) scheme. Experimental analyses indicate that SAA method provides better results than the greedy method without worsening the solution time performance. © 2017, Springer-Verlag Berlin Heidelberg.TEYDEB-1507-7150022This research has been supported by T?B?TAK (The Scientific and Technological Research Council of Turkey) under the Grant no: TEYDEB-1507-7150022