{"title":"丑闻监视器:用于应急管理的社交媒体数据的实时处理和可视化","authors":"Xiubo Zhang, Stephen Kelly, K. Ahmad","doi":"10.1109/ARES.2016.81","DOIUrl":null,"url":null,"abstract":"The use of social media platforms has grown dramatically in recent times. Combined with the rise of mobile computing, users are now more connected and spend more of their time online. Social media has been used during emergency events where the public and authorities have used it as a form of communication and to receive information. Due to this, emergency managers and first responders can use this information to increase their awareness about an on-going crisis and aid decision making. The challenge here lies in processing this deluge of information and filtering it for insights that are useful for this purpose. This paper presents the Slandail Monitor, a system for harvesting and filtering a social media stream for emergency related social media data. Spatial and temporal data attached to each message are used with the analysed content of each message to summarise on-going emergency events as reported on social media. This information is combined with a visualisation component to allow a user to quickly assess an event by location, time, and by topic. Issues about ethical data harvesting and privacy are also addressed by the system in a computational way by logging potentially sensitive information in the intrusion index.","PeriodicalId":216417,"journal":{"name":"2016 11th International Conference on Availability, Reliability and Security (ARES)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"The Slandail Monitor: Real-Time Processing and Visualisation of Social Media Data for Emergency Management\",\"authors\":\"Xiubo Zhang, Stephen Kelly, K. Ahmad\",\"doi\":\"10.1109/ARES.2016.81\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The use of social media platforms has grown dramatically in recent times. Combined with the rise of mobile computing, users are now more connected and spend more of their time online. Social media has been used during emergency events where the public and authorities have used it as a form of communication and to receive information. Due to this, emergency managers and first responders can use this information to increase their awareness about an on-going crisis and aid decision making. The challenge here lies in processing this deluge of information and filtering it for insights that are useful for this purpose. This paper presents the Slandail Monitor, a system for harvesting and filtering a social media stream for emergency related social media data. Spatial and temporal data attached to each message are used with the analysed content of each message to summarise on-going emergency events as reported on social media. This information is combined with a visualisation component to allow a user to quickly assess an event by location, time, and by topic. Issues about ethical data harvesting and privacy are also addressed by the system in a computational way by logging potentially sensitive information in the intrusion index.\",\"PeriodicalId\":216417,\"journal\":{\"name\":\"2016 11th International Conference on Availability, Reliability and Security (ARES)\",\"volume\":\"55 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 11th International Conference on Availability, Reliability and Security (ARES)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ARES.2016.81\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 11th International Conference on Availability, Reliability and Security (ARES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ARES.2016.81","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Slandail Monitor: Real-Time Processing and Visualisation of Social Media Data for Emergency Management
The use of social media platforms has grown dramatically in recent times. Combined with the rise of mobile computing, users are now more connected and spend more of their time online. Social media has been used during emergency events where the public and authorities have used it as a form of communication and to receive information. Due to this, emergency managers and first responders can use this information to increase their awareness about an on-going crisis and aid decision making. The challenge here lies in processing this deluge of information and filtering it for insights that are useful for this purpose. This paper presents the Slandail Monitor, a system for harvesting and filtering a social media stream for emergency related social media data. Spatial and temporal data attached to each message are used with the analysed content of each message to summarise on-going emergency events as reported on social media. This information is combined with a visualisation component to allow a user to quickly assess an event by location, time, and by topic. Issues about ethical data harvesting and privacy are also addressed by the system in a computational way by logging potentially sensitive information in the intrusion index.