Crowd Intelligence Participation in Digital Ecosystem: Systematic Process for Driving Insight from Social Network Services Data

In an increasingly fast paced of digitalization, Social Network Services (SNSs) acting as a major component in the transformation process. Meanwhile, progress of computational power and data analytic techniques necessitate to visit the massive data generated from SNSs for accurate insights for better decision making. In this research, we propose a systematic process for analyzing SNSs data utilizing the advancement in text analytics and topic modeling. Furthermore, the proposed methodology put into practice for driving insight from crowed intelligence contribution in Twitter regarding the sample case of Fukushima incident. The relevant tweets retrieved, preprocessed and textually analyzed to reveal the topical evolutionary pattern of discussions. The topical analysis and visualization indicates more coherent and less topic proximity in discussion over time.