Maximizing Diversity and Persuasiveness of Opinion Articles in Social Networks

The formation and evolution of opinions in social networks is a complex process affected by the interplay of different elements that incorporate peer interaction in social networks and the diversity of information to which each individual is exposed. Taking a step in this direction, we propose a model which captures the dynamic of both opinion and relationship in this paper. It not only considers the direct influence of friends but also highlights the indirect effect of group when individuals are exposed to new opinions. And it allows nodes which represent users of social networks to slightly adjust their own opinion and sometimes redefines friendships. A novel problem in social network whose purpose is simultaneously maximizing both the diversity and persuasiveness of new opinions that individuals have access to is formulated. This problem is proved to be NP-hard and its objective function is neither submodular nor supermodular. However, we devise an approximation algorithm based on the sandwich framework. And the influence of different seed selection strategies is experimentally demonstrated.