Recently, various SNSs (social networking services) such as Twitter1, Facebook2, and so on, have gained wide use. These enable access to a wide rage of information related to the real world, through analysis of texts posted on such SNSs. For example, when many people tweet about an earthquake, we can typically infer that an earthquake has occurred in the real world. In this study, we consider the acquisition of such information as social sensor usage, and call the generated data social sensor data. We can exploit social sensor data for many applications, and easily reuse the data by sharing analytical programs to develop new types of social sensors. However, there currently exists no suitable system for sharing them. In this study, we designed and implemented a system to generate and share such social sensor data, called the S3 (S-cube, social sensor sharing) system; then compared the features of the S3 system with those of other data- and analytical program-sharing systems, and assessed the relative effectiveness of the S3 system in sharing social sensor data.
['Keisuke Nakashima', 'Masahiro Yokoyama', 'Yuki Taniyama', 'Tomoki Yohshihisa', 'Takahiro Hara']
S3 System: A System for Sharing Social Sensor Data and Analytical Programs