Measuring political information: novel method for estimating the information content of political communication
PS8-1
Presented by: Michal Parizek, Jakub Tesař
We present the contours of a novel methodological framework for estimating quantitatively the information content of political communication. The framework is rooted in information theory (IT) and centred at one of its building blocks, the notion of communication entropy as the proper measure of information. We seek to adapt this IT framework and develop an applicable measure of the information transmitted over political communication. Substantially, our approach highlights the principal difference between the amount of communication activity and the actual volume of information transmitted. We illustrate the applicability of the framework by analysing how online media in the US report on Canada, China, and India. We use a dataset of close to 800 000 online news in 2019, analyzed using natural language processing techniques, to show how reporting on these three countries varies in information content. The highest number of news reports on China. Yet, applying our framework, we find that the total volume of information is highest for India, even though news on China is more frequent. Further, reporting on Canada carries the highest average information content. Our framework enables us to identify and quantify these differences.