Diffusion of information can be found in any social network, either it be a small network of co-workers or large as social networking applications like Facebook, Twitter, LinkedIn,etc. In this paper, we propose a system to analyse the correlation amongst the group of people and build the influential relationship amongst them, which is based on the diffusion of emotions within this network. Actually we track the action and reaction in the form of facial emotions of all the participants in the network, and based on which we discover the influence among them. Later this influential relationship in the network is represented in weighted directed graph; where weight represents the extent of influence between each pair of nodes. Moreover, considering the robustness and scalability of the proposed algorithm with the varying size of the network, we have incorporated multiagent paradigm in our model. Further, our results were validated by analysing a scripted discussion done in our laboratory. Such knowledge of the influences among the participants of the network,could be used to find the influential individual; further can find many applications such in consensus, negotiation, viral marketing, etc.
|Number of pages||17|
|Journal||International Journal of Information Technology|
|Publication status||Published - 2016|
- facial feature extraction
- correlation analysis