Developing IQJournalism: An Intelligent Advisor for Predicting the Perceived Quality in Greek News Articles

Technological developments and the integration of social media into journalistic practices have transformed the media landscape, changing how information is gathered, produced, and shared. This evolution poses challenges, including the lack of clear guidelines and practical tools for ensuring the quality of digital news content. To address these issues, IQJournalism, an intelligent quality prediction advisor, was developed. This paper outlines the methodology for the development of IQJournalism, a platform that leverages advanced AI technologies to process Greek news articles and provide real-time editing recommendations on various dimensions, including language quality, subjectivity level, emotionality, entertainment, and social media engagement. First, a qualitative study was conducted through semi-structured, in-depth interviews with 20 experts, academic researchers and media professionals to identify indicators of perceived quality in journalism. These insights were then transformed into measurable features, which served as training data for explainable machine learning-based models for quality categorization and prediction. Finally, the IQJournalism platform was designed following a user-centered iterative process that included prototyping, testing, and redesigning. The innovative approach aims to serve as a valuable tool for improving journalistic quality, contributing to more reliable and engaging online news content. Importantly, the platform is not limited to the journalistic sector, but can also be used to optimize content in various areas, such as marketing, political, and strategic communication, supporting editors seeking to improve the quality and impact of their writing.