Computer Science has affected almost all fields of human knowledge, contributing to scientific advances in many branches of Natural and Social Sciences. Journalism is one of the fields that is benefiting of the advance of computer science. Among the journalistic concepts that can be analyzed computationally is News Value. Novelty is one of the most important news value. A possible approach to get novelty elements in a story considers word frequency, through of the capacity to collect and analyze massive amounts of data. In this paper, we use the News Coverage Index dataset (NCI), maintained by the Pew Research Center, to analyze the novelty dynamics of news coverage, using the novelty signatures proposed by [12]. As a definition of novelty, we used the first appearance of a new lead newsmaker. Results show a good fit of the model to the dataset. Furthermore, an analysis by media sector and broad topic shows interesting insights for the analysis of media coverage.