In this research, we propose a new concept for social media analysis called Social Sensor, which is an innovative design attempting to transform the concept of a physical sensor in the real world into the world of social media with three design features: manageability, modularity, and reusability. The system is a case-centered design that allows analysts to select the type of social media (such as Twitter), the target data sets, and appropriate social sensors for analysis. By adopting parameter templates, one can quickly apply the experience of other experts at the beginning of a new case or even create oneâ€™s own templates. We have also modularized the analysis tools into two social sensors: Language Sensor and Text Sensor. A user evaluation was conducted and the results showed that usefulness, modularity, reusability, and manageability of the system were all very positive. The results also show that this tool can greatly reduce the time needed to perform data analysis, solve the problems encountered in traditional analysis process, and obtained useful results. The experimental results reveal that the concept of social sensor and the proposed system design are useful for big data analysis of social media.
International Journal of Electronic Commerce Studies, 7(1), 77-94