How Effectively Can We Form Opinions?

People make decisions and express their opinions according to their communities. An appropriate idea for controlling the diffusion of an opinion is to find influential people, and employ them to spread the desired opinion. We investigate an influencing problem when individuals' opinions are affected by their friends due to the model of Friedkin and Johnsen [4]. Our goal is to design efficient algorithms for finding opinion leaders such that changing their opinions has great impact on the overall opinion of the society. We define a set of problems like maximizing the sum of individual opinions or maximizing the number of individuals whose opinions are above a threshold. We discuss the complexity of the defined problems and design optimum algorithms for the non NP-hard variants of the problems. Furthermore, we run simulations on real-world social network data and show our proposed algorithm outperforms the classical algorithms such as degree-based, closeness-based, and pagerank-based algorithms.