What Readers Want

A new study has analyzed the millions of choices available to readers of online news and created a model to find out ‘what makes people click’.

The researchers developed a model of “news appeal” based on the words contained in an article’s title and text intro, which is what a reader uses to choose to click on a story. The study by academics at the University of Bristol’s Intelligent Systems Laboratory is published in Pattern recognition - applications and methods. The aim of the study was to model the reading preferences of the audiences of 14 online news outlets using machine learning techniques. The models, describing the appeal of a given article to each audience, were developed by linear functions of word frequencies. The model compared articles that became “most popular” on a given day in a given outlet with articles that did not. The research, led by Nello Cristianini, Professor of Artificial Intelligence, identified the most attractive keywords, as well as the least attractive ones, and explained the choices readers made.