{"title":"Data Analysis of Various Terrorism Activities Using Big Data Approaches on Global Terrorism Database","authors":"Kashish Bhatia, B. Chhabra, Manish Kumar","doi":"10.1109/PDGC50313.2020.9315784","DOIUrl":null,"url":null,"abstract":"The field of data science is getting wide day by day and more areas are using this concept. This paper uses the concept of data science for analyzing patterns of terrorism globally. We use the “Global Terrorism Database (GTD)” having information of terrorist attacks around the world from 1970 to 2017. The data was preprocessed and we use “Hive Query Language (HiveQL)” and Hadoop concepts to make various predictions out of the database. HiveQL is run by intergrating with Hadoop which is installed on a linux system. Various interesting findings were made from this database which are represented in the form of queries that were shot on the database. The queries were decided upon by framing a few questions and finding suitable answers. The results obtained are presented graphically using tableau and python for a better understanding of the reader. In the last section, various inferences were drawn from the results obtained.","PeriodicalId":347216,"journal":{"name":"2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PDGC50313.2020.9315784","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The field of data science is getting wide day by day and more areas are using this concept. This paper uses the concept of data science for analyzing patterns of terrorism globally. We use the “Global Terrorism Database (GTD)” having information of terrorist attacks around the world from 1970 to 2017. The data was preprocessed and we use “Hive Query Language (HiveQL)” and Hadoop concepts to make various predictions out of the database. HiveQL is run by intergrating with Hadoop which is installed on a linux system. Various interesting findings were made from this database which are represented in the form of queries that were shot on the database. The queries were decided upon by framing a few questions and finding suitable answers. The results obtained are presented graphically using tableau and python for a better understanding of the reader. In the last section, various inferences were drawn from the results obtained.
数据科学领域日益广泛，越来越多的领域正在使用这个概念。本文使用数据科学的概念来分析全球恐怖主义的模式。我们使用“全球恐怖主义数据库”(GTD)，该数据库拥有1970年至2017年全球恐怖袭击的信息。我们对数据进行了预处理，并使用“Hive Query Language (HiveQL)”和Hadoop概念从数据库中做出各种预测。HiveQL与安装在linux系统上的Hadoop集成运行。从这个数据库中得出了各种有趣的发现，这些发现以在数据库上拍摄的查询的形式表示。这些问题是通过构建几个问题并找到合适的答案来确定的。得到的结果用图表和python图形化地呈现，以便读者更好地理解。在最后一节中，从得到的结果中得出了各种推论。
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
