Our new project is called iQJournalism : An Intelligent Advisor Predicting Perceived Quality in Journalism

Our new project is called iQJournalism : An Intelligent Advisor Predicting Perceived Quality in Journalism

Patterns of news consumption are changing drastically due to the rapid development of new media combined with the explosion of social network sites. Media organizations changed the way they publish their content, since nowadays the relationship between journalists and the audience is less straightforward. The evaluation of journalistic articles through user interactions has influenced the decision-making processes within the newsrooms by making clicks, shares, and the overall user engagement the key quantitative parameters for measuring the success of a news story.   At this point comes the contribution of the proposed project, since -to the best of our knowledge- there are no clear rules and tools on how to write a journalistic piece that will be published online, something that often leads to “click-baiting” and fake news.   Recently, the New Technologies Laboratory has conducted extensive research on the aspects of  perceived quality of journalistic articles, which largely depends on the reader’s judgment. The initial findings show that polarity, article’s lenght, text-to-image ratio and the number of followers a journalist has affect, among other things, the perceived quality of the online news stories.   Building on the already conducted research and the relevant theoretical background, the current proposal aims to create an innovative product for the Greek digital mass media market: An Intelligent Advisor for Quality in Journalism, which will guide editors real time on the expected success and quality of their piece of writing. The creation of the Intelligent Platform will set a number of key objectives, such as the quality enhancement of journalistic articles, the amplification of the dissemination of journalistic texts and the further development of Machine Learning in the field of perceived quality of journalistic articles.  

October 2021 – December 2023

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