Social Media Sentiment Analysis for Public Policy Decision Making
Big Data Analytics Approach for Democratic Governance
Penulis: Dr. Maya Sari, S.Sos., M.A., Prof. Ir. Andi Prasetyo, M.Si., Dr. Fitri Handayani, S.Kom., M.T.
Informasi Konferensi
Konferensi: International Conference on Digital Society and Governance (ICDSG)
Tanggal: 2024-07-18
Lokasi: Bali, Indonesia
Penyelenggara: International Association for Digital Society Research
Publisher: Elsevier
Halaman: 567-574
Abstrak
Abstract
This study develops a comprehensive methodology for social media sentiment analysis to support public policy decision-making processes. The research leverages big data analytics and machine learning techniques to extract meaningful insights from citizen opinions expressed through social media platforms.
Research Methodology:
- Multi-platform social media data collection and preprocessing
- Advanced natural language processing for Indonesian text analysis
- Real-time sentiment classification and trend analysis
- Policy impact assessment through sentiment tracking
Case studies on three major policy initiatives show 85% accuracy in predicting public reception and 70% improvement in policy adjustment effectiveness when informed by sentiment analysis results.
Kata Kunci
sentiment analysis, social media, public policy, big data, democratic governance, computational social science