Alvi Syahrina, Media Wahyudi Askar, Margareta Hardiyanti, Mochamad Satria Riza Permana and Kayla Queenazima Santoso
This study presents the development of Unitrend, a big data–driven platform designed to assist policymakers in monitoring and analyzing online news media in real time. In the information age, where vast amounts of digital content are produced continuously, Unitrend provides a solution for evidence-based decision making. The platform integrates technologies such as web scraping, natural language processing (NLP), sentiment analysis, and named entity recognition (NER) to extract key entities, identify public sentiment, and reveal emerging trends from major Indonesian news outlets. Through interactive data visualisation dashboards, Unitrend enables decision-makers to gain deeper insights into public discourse, respond quickly to changing conditions, and enhance the effectiveness of policy formulation.
The paper outlines Unitrend’s system architecture, which consists of four main components: data acquisition, data processing and analysis, data storage, and data visualisation. The system continuously collects data from multiple online media sources, processes it using tools such as the VADER sentiment lexicon and the BERT-base-NER model, and presents the results in dynamic visual formats like time-series charts and word clouds. The research highlights Unitrend’s potential to transform data into actionable intelligence for public administration, while also acknowledging its current limitations, including data accuracy issues, technical challenges in web scraping, and the absence of predictive analytics. Overall, the study demonstrates how Unitrend contributes to more transparent, adaptive, and data-driven governance.
Reference:
Syahrina, A., Askar, M. W., Hardiyanti, M., Permana, M. S. R., & Santoso, K. Q. (2025). Informing Decision Makers: Development of Online News Media Monitoring and Visualisation. Electronic Government, 21(6), 613–633. Inderscience Enterprises Ltd.
Link:
https://www.inderscienceonline.com/doi/10.1504/EG.2025.149231