IDEIA: A Generative AI-Based System for Real-Time Editorial Ideation in Digital Journalism
Victor B. Santos, Cau\~a O. Jord\~ao, Leonardo J. O. Ibiapina, Gabriel M. Silva, Mirella E. B. Santana, Matheus A. Garrido, Lucas R. C. Farias

TL;DR
This paper introduces IDEIA, a generative AI system that enhances real-time editorial ideation in digital journalism by integrating trend analysis and automated content suggestions, significantly improving efficiency.
Contribution
The paper presents a novel modular AI system that combines trend monitoring and content generation for journalism, demonstrating practical benefits and discussing ethical considerations.
Findings
Up to 70% reduction in ideation time
Improved editorial productivity and quality
Scalable architecture for newsroom integration
Abstract
This paper presents IDEIA (Intelligent Engine for Editorial Ideation and Assistance), a generative AI-powered system designed to optimize the journalistic ideation process by combining real-time trend analysis with automated content suggestion. Developed in collaboration with the Sistema Jornal do Commercio de Comunica\c{c}\~ao (SJCC), the largest media conglomerate in Brazil's North and Northeast regions, IDEIA integrates the Google Trends API for data-driven topic monitoring and the Google Gemini API for the generation of context-aware headlines and summaries. The system adopts a modular architecture based on Node.js, React, and PostgreSQL, supported by Docker containerization and a CI/CD pipeline using GitHub Actions and Vercel. Empirical results demonstrate a significant reduction in the time and cognitive effort required for editorial planning, with reported gains of up to 70\% in…
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Taxonomy
TopicsMedia Studies and Communication · Big Data and Digital Economy · Computational and Text Analysis Methods
