Assessing the Quality of Online News Articles as References for an Encyclopaedia Entry

The quality of online news articles is decisive both for a reliable perception of their informativeness and for including them as a reference when creating an encyclopaedia entry for a public attention event. Tackling the enormous volume, variety and complexity of different articles disseminated online, 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 utilizes the factual density as a quality measure of the information reported on the missing Malaysia Airliners Flight 370 as a public attention event in two instances, considering the coverage during the initial investigation and the reporting marking the one year anniversary since the plane got missing. The results suggest that the factual density can be utilized in creating a high-quality encyclopaedia entry, however, under strict conditions in terms of increased confidence level of the automated factual extraction.