Maximizing positive opinion influence using an evidential approach

Abstract

In this paper, we propose a new data based model for influence maximization in online social networks. We use the theory of belief functions to overcome the data imperfection problem. Besides, the proposed model searches to detect influencer users that adopt a positive opinion about the product, the idea, etc, to be propagated. Moreover, we present some experiments to show the performance of our model.

References in corpus (1)

• Dynamic time warping distance for message propagation classification in Twitter

Cited by in corpus (1)

• A reliability-based approach for influence maximization using the evidence theory