Keisuke Nakashima, Masahiro Yokoyama, Y. Taniyama, T. Yoshihisa, T. Hara
{"title":"S3 System: A System for Sharing Social Sensor Data and Analytical Programs","authors":"Keisuke Nakashima, Masahiro Yokoyama, Y. Taniyama, T. Yoshihisa, T. Hara","doi":"10.1145/3004010.3004037","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":406787,"journal":{"name":"Adjunct Proceedings of the 13th International Conference on Mobile and Ubiquitous Systems: Computing Networking and Services","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Adjunct Proceedings of the 13th International Conference on Mobile and Ubiquitous Systems: Computing Networking and Services","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3004010.3004037","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
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.
最近,各种社交网络服务(sns)如Twitter1、Facebook2等得到了广泛的应用。通过分析这些社交网站上发布的文本,这些网站能够获得与现实世界有关的广泛信息。例如,当许多人在推特上谈论地震时,我们通常可以推断出地震发生在现实世界中。在本研究中,我们考虑社会传感器使用等信息的获取,并将生成的数据称为社会传感器数据。我们可以将社交传感器数据用于许多应用,并通过共享分析程序轻松重用数据以开发新型社交传感器。然而,目前还没有合适的系统来共享它们。在本研究中,我们设计并实现了一个生成和共享社交传感器数据的系统,称为S3 (S-cube, social sensor sharing)系统;然后比较了S3系统与其他数据和分析程序共享系统的特征,并评估了S3系统在共享社会传感器数据方面的相对有效性。