Sentiment analysis suptech application to monitor web and social media content on digital assets and cryptocurrency.
Digital Transformation Solutions (DTS) developed, tested, integrated, and delivered a prototype sentiment analysis tool designed to monitor web and social media platforms for OJK, with support from ADB. The tool focused on digital assets and cryptocurrency activities and was built as a stand-alone product with the capability to integrate with broader suptech solutions or other relevant internal systems, ensuring it met stakeholder requirements and regulatory needs.
The project began with the design and development of a functional prototype. We conducted a thorough requirements-gathering process, collaborating closely with stakeholders—including regulatory bodies, market participants, and other relevant actors—to define the technical, functional, and performance specifications for the tool. The architecture was designed with scalability, performance, and security in mind. The prototype incorporated machine learning algorithms and other processing techniques to analyse data from web and social media sources, and featured a user-friendly interface with dashboards and visualisations to present sentiment analysis results clearly and intuitively.
Upon completion of the prototype, we carried out User Acceptance Testing (UAT) to ensure the tool met stakeholder expectations and requirements. This phase involved executing a detailed UAT plan, working closely with stakeholders to validate functionality, usability, and performance. Issues identified during testing were resolved, and feedback was incorporated into the final version.
The sentiment analysis tool was designed to be extensible and capable of integrating with other suptech solutions and relevant internal systems. We defined integration requirements, developed APIs and other integration points, and conducted integration testing to ensure seamless interoperability with existing—and potentially future—systems. All integration work adhered to necessary data formats, communication protocols, and security standards, with comprehensive documentation provided to support future upgrades and maintenance.
Finally, we established a reporting and monitoring framework to track both development progress and post-deployment performance. Progress reports were delivered at key milestones, and after deployment, we monitored the tool’s effectiveness against metrics such as sentiment accuracy, data processing speed, and system uptime. A feedback loop enabled continuous optimisation, with post-deployment support provided for troubleshooting, maintenance, and periodic updates.
