IMEXT:一种从tweet中提取地理定位图像的方法和系统-案例研究分析

C. Francalanci, Paolo Guglielmino, Matteo Montalcini, Gabriele Scalia, B. Pernici
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引用次数: 13

摘要

从社交网络中提取有用的信息提出了一些挑战,这些挑战仍然是有待研究的问题。本文主要研究从推文中提取地理定位图像以支持应急响应的问题。本文讨论了Tweet的分析过程,重点是对Tweet的选择,根据Tweet的文本内容对Tweet进行地理定位,以及对经过地理定位的Tweet所链接的图像进行后续分析。基于2016年8月意大利中部地震发生后两天内发布的推文,已经建立了一个原型系统并进行了案例研究测试。结果表明,关注由地理定位推文链接的图像是识别有助于应急响应的有用信息的良好标准。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
IMEXT: A method and system to extract geolocated images from Tweets — Analysis of a case study
Extracting useful information from social networks raises several challenges that still represent open research issues. In this paper we focus on the problem of extracting geolocated images from Tweets to support emergency response. A Tweet analysis process is discussed, focusing on the selection of posts, their geolocation based on their text content, and the subsequent analysis of the images linked by geolocated tweets. A prototype system has been built and tested on a case study based on the Tweets posted in the two days after the earthquake that occurred in Central Italy in August 2016. Results indicate that focusing on images linked by geolocated tweets represents a good criterion to identify useful information that can aid emergency response.
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