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Exploring Bot Pervasiveness in Global Cities using Publicly Available Volunteered Geographic Information

机译:使用公开可自愿地理信息探索全球城市的机器人普及

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Effective crisis management and response heavily relies on up-to-date and trustworthy information. Near real-time, volunteered geographic information (VGI) has previously been shown to be instrumental during disaster response by helping direct resources, create communication channels between the affected, etc. Trustworthiness continues to be a challenge when leveraging crowd sourced data, as quality information directly impacts the effectiveness of response. Previous research has demonstrated cloud-based VGI collection, storage, presentation, and bot mitigation using open source technologies and freely available web services. Alas, the technology was deployed as a prototype for small urban areas in the United States. This research explores bot pervasiveness in several global cities that have previously suffered a catastrophic event and/or are at risk for a future crisis event. The existence of non-trustworthy information in social media data has always been a known issue, taking steps to quantify the presence of bots in Twitter data can allow an end-user to more holistically understand their dataset.
机译:有效的危机管理和响应大量依赖于最新和值得信赖的信息。近乎实时,志愿地理信息(VGI)之前已被证明在灾害响应期间通过帮助直接资源,在受影响的沟通渠道之间创建沟通渠道等。值得信赖性在利用人群源数据时继续是一个挑战,如优质信息直接影响反应的有效性。以前的研究已经展示了基于云的VGI收集,存储,演示和机器人缓解,使用开源技术和自由可用的Web服务。 ALAS,该技术被部署为美国小城区的原型。这项研究探讨了几个全球城市的机器人普及,以前遭受了灾难性事件和/或面临未来危机事件的风险。在社交媒体数据中存在非值得信赖的信息一直是一个已知的问题,采取措施来量化Twitter数据中的机器人的存在,可以允许最终用户更全面地理解他们的数据集。

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