Named Entity Recognition (NER) is a challenging and widely studied task that involves detecting and typing entities in text.
Furthermore, the reliability-based influence measure is used with an influence maximization model to select a set of users that are able to maximize the influence in the network.
In this paper, we are mainly interested in the classification of social messages based on their spreading on online social networks (OSN).
In this paper, we propose two evidential influence maximization models for Twitter social network.
Social and Information Networks
In this paper, we propose a new data based model for influence maximization in online social networks.
We tested our classifier on a real word network that we collected from Twitter, and our experiments show the performance of our belief classifier.