A Social Sensor Visualization System for a Platform to Generate and Share Social Sensor Data
Zennosuke Aiko, Keisuke Nakashima, Tomoki Yoshihisa, Takahiro Hara · 2018
We can get real-world information (social sensor data) by analyzing posts on social networking services (SNSs), which have become popular in recent years. We are studying and developing a system to generate and share social sensor data and social sensors (programs to analyze posts on SNSs) among users. Descriptions of previously created social sensors such as analysis programs are helpful for creations of new social sensors. When users search previously created social sensors in conventional S^3 systems, search results are shown in list form without indicating relevances between social sensors. Therefore, users need to check descriptions of many social sensors until finding helpful descriptions. This annoys users to create new social sensors. By reducing the number of social sensors to be checked, users can find helpful descriptions easier. In this research to achieve fast search, we designed and implemented a system to visualize relevances between social sensors. The proposed system regards that previously referenced social sensors are relevant and also that social sensors with high similarity in descriptions are relevant. The proposed visualization system shows relevances between social sensors by representing social sensors as nodes connected to their referenced social sensors by edges.