• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>International Conference on Mathematics, Computational Sciences and Statistics >Public health on social media: Using Instagram posts for investigating dengue hemorrhagic fever in Indonesia
【24h】

Public health on social media: Using Instagram posts for investigating dengue hemorrhagic fever in Indonesia

机译：社交媒体上的公共卫生：使用Instagram帖子来调查印度尼西亚的登革热出血热

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Dengue Hemorrhagic Fever (DHF), an acute capillary leak syndrome caused by dengue virus, is one of the major public health problems in Indonesia. Several major DHF outbreaks have occurred, and the incidence rate has increased from year to year. The increasing use of social media for health-related activities and the geolocation social media data can be leveraged to enhance the current surveillance system for controlling communicable diseases, including DHF. This study explores Instagram, one of the most popular social media in Indonesia, to analyze posts about DHF toward improving the surveillance system. We extract Instagram posts in 2017 - 2018 with geolocation and date-time value, that contained one or more DHF keywords in Indonesian language (i.e., demam berdarah dengue, demam berdarah, dengue, Aides aegypti, and fogging), resulting in 665 posts in dataset 2017 and 976 in dataset 2018. The preprocessing of the dataset includes tokenization, word normalization, stop word removal, stemming, and building the term-document matrix. The training dataset is labeled into news, education and information, and other classes, and the K- nearest neighbors (KNN) is applied to classify the DHF posts. The accuracy of the KNN classifier is 71% for the 2017 dataset and 77% for the 2018 dataset. For the deployment, we perform spatial analysis and compare the results with the actual DHF cases from the Ministry of Health of Indonesia. The spatial analysis results report that 17 provinces reveal similar changes between the number of DHF posts on Instagram and the number of actual cases from 2017 to 2018, while 17 other provinces reveal the opposing changes. The results and findings of this study show that Instagram posts may contribute to enhance the current surveillance system. For example, the frequency of Instagram posts and its sharp increase may indicate unusual events about the DHF situation in a specific province.
机译：登革热出血热（DHF），急性毛细血管泄漏综合征是登革热病毒，是印度尼西亚的主要公共卫生问题之一。发生了几个主要的DHF爆发，发病率从一年增加到。可以利用越来越多地利用社交媒体对健康相关活动和地理位置社交媒体数据，以增强控制传染病，包括DHF的电流监测系统。这项研究探讨了印度尼西亚最受欢迎的社交媒体之一的Instagram，分析了关于改善监视系统的DHF的帖子。我们在2017年提取Instagram帖子与地理位置和日期时间价值，其中包含印度尼西亚语言的一个或多个DHF关键字（即Demam Berdarah登革热，德曼·贝尔德拉，登革热，助攻AEGYPTI和雾化），导致665篇帖子DataSet 2017和976在DataSet 2018中。数据集的预处理包括标记化，字标准化，停止字删除，串鸣和构建术语文档矩阵。培训数据集标记为新闻，教育和信息和其他类，并应用K-最近的邻居（KNN）来分类DHF帖子。 2017 DataSet的KNN分类器的准确性为71％，2018年数据集的77％。对于部署，我们进行空间分析，并将结果与​​印度尼西亚卫生部的实际DHF案例进行比较。空间分析结果报告称，17个省份揭示了Instagram上的DHF职位数与2017年至2018年的实际案件数量之间的类似变化，而17个其他省份揭示了反对的变革。本研究的结果和调查结果表明，Instagram帖子可能有助于提高当前监测系统。例如，Instagram帖子的频率及其急剧增加可能表示特定省份的DHF情况的异常事件。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号