We specifically test the claim that new information decoupling behavior of media can be used to reliably detect change in news media content originating in a negative event, using a Bayesian approach to change point detection.
Theory of Mind (ToM) is considered crucial for understanding socio-cognitive abilities and impairments. However, verbal theories of the mechanisms underlying ToM are often criticized as under-specified and mutually incompatible. This leads to measures of ToM being unreliable, to the degree where even canonical experimental tasks do not require representation of others’ mental states. In order to help meet these challenges we introduce the Python package tomsup.
In this paper, we use legacy print media to empirically derive the principle News Information Decoupling (NID) that functions as an information signature of culturally significant catastrophic event.
Digitization has changed flow music radio in several ways. The aim of the article is twofold: 1) To describe the methodological process and challenges for developing a model for large-scale Speech-Music discrimination analysis on radio data. 2) To discuss and critically compare the methods, results, strengths and shortcomings of the qualitative and the quantitative analysis, respectively.
Political biases in News media is traditionally estimated using based on the voting habits of the newspaper's readers. This method does not establish the direction of causation, but only a correlation between news media and reader. Using sentiment analysis we show that Danish newspapers report significantly different on Danish parties on either side of the political spectrum.