Filipo Sharevski, Purdue University, USA
In circumstances where the receptivity of the online news is affected by the media bias in covering public attention events, the quality of the textual component is of pervasive importance for a reliable perception of their informativeness. Aware of this threat, several natural language processing techniques have been developed for the purpose of capturing the quality of the web content based on the concepts of objectivity classification and stylometric features, knowledge maturing, factual density, or simple word count. This paper explores the appropriateness of the factual density as an adequate quality measure of the information reported on the missing Malaysia Airliners Flight 370 as a public attention event. The results suggest that the factual density needs to be applied under strict conditions in terms of increased confidence level of the textual news content, if its substance is a subject of capitalization as a referent source of information.
Factual Density, Natural Language Processing, Text Informativeness