Computer scientists have analysed over a million news articles in 22 languages to pinpoint what fact

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The aim of the study was to model the reading preferences for the audiences of 14 online news outlets using machine vancouver island bc whalewatch tours learning techniques. The models, vancouver island bc whalewatch tours describing the appeal of an article to each audience , were developed by linear functions of word frequencies. The models compared articles that became "most popular" on a given day in a given outlet with articles that did not.
The researchers examined millions of article vancouver island bc whalewatch tours pairs, collected over nearly eighteen months. The models analysed user choices, vancouver island bc whalewatch tours choices were then used to compare both the audiences vancouver island bc whalewatch tours and the contents of various news outlets.
The researchers found that there is a significant correlation between the demographic profiles of audiences and their preferences. They also found that content appeal is related both to writing style - with more sentimentally charged language being preferred, and to content with " public affairs " topics, such as "finance" and "politics", being less preferred.
More information: Paper: Modelling and Explaining Online News Preferences, Elena Hensinger, Ilias Flaounas, Nello Cristianini, In Collection: Pattern Recognition - Applications and Methods, Springer Berlin Heidelberg.
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