Syahrina, Alvi and Askar, Media Wahyudi and Hardiyanti, Margareta and Permana, Mochamad Satria Riza and Santoso, Kayla Queenazima (2025) Informing decision makers: development of online news media monitoring and visualisation. Electronic Government, 21 (6). 613 - 633. ISSN 1740-7494
Full text not available from this repository. (Request a copy)Abstract
As information continues to be generated online, the volume of ‘big data’ is rapidly increasing, offering potential for strategic decision-making across industries, including public administration. The online news media, as a source of real-time information, have transformed the way policymakers access and respond to public sentiment and emerging issues. In this context, the need for advanced tools to monitor and analyse vast streams of online news has become crucial. This paper introduces Unitrend, a platform designed to facilitate data-driven decision-making by offering real-time insights through advanced data processing, data analysis, and visualisation technologies. Unitrend aggregates news data, conducts sentiment analysis, and tracks key entities, providing policymakers with a comprehensive understanding of trends and public reactions. This research explores Unitrend’s system architecture and methodologies, highlighting its potential benefits and limitations in fostering responsive and informed policy development.
| Item Type: | Article |
|---|---|
| Additional Information: | Cited by: 0 |
| Uncontrolled Keywords: | news media monitoring; big data analytics; natural language processing; NLP; sentiment analysis; named entity recognition; NER; web scraping; evidence-based policy making |
| Subjects: | H Social Sciences > HD Industries. Land use. Labor H Social Sciences > HN Social history and conditions. Social problems. Social reform |
| Divisions: | Faculty of Political and Social Sciences > Public Policy and Management |
| Depositing User: | Nurrochmah Febrianti Nadyasari SHum |
| Date Deposited: | 08 Sep 2026 04:29 |
| Last Modified: | 08 Sep 2026 04:29 |
| URI: | https://ir.lib.ugm.ac.id/id/eprint/29691 |
