Simulating the spread of opinions in online social networks when targeting opinion leaders
An increasing number of people are joining online social networks. By interacting with each other, network members influence one anothers opinion. These influencing effects can be utilized by marketing. A wave of influence can be triggered by addressing only a few opinion leaders in the network. Targeting the right opinion leaders is a big challenge. This paper presents a new approach which simulates the spread of opinions when influencing certain opinion leaders. In contrast to other approaches, the influencing effects are not assumed but revealed by real data. The principles of opinion formation are detected by ant mining algorithms before they are applied to simulate the spread of opinions. The approach is applied to an online gaming community and provides valuable insights for marketing.
opinion leaders influence opinion mining diffusion social network analysis ant algorithms