文本大数据分析:探索API机会:互联网作为全球存储——如何从暗数据中获得态势感知

O. Kolesnichenko, Gennady Smorodin, D. Yakovleva, L. Mazelis, O. Zhurenkov, Yuriy Kolesnichenko
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引用次数: 2

摘要

文本大数据分析研究«第三波»描述。利用API从互联网开放文本资源中提取多个关键词短语的形态矩阵。本文从全球互联网受众形成“人-信息技术”系统的角度对研究结果进行了分析,从而研究了全球社会的三个行为层次。1级-国家在互联网上的活动。第二层-各国的技术演变。第三级:国家对破坏性压力因素的反应。一级调查采用聚类分析。Level 2的调查使用了Simon Wardley的Value Chain Map。三级调查采用不同组关键词短语的百分比比例图。文章的重点是欧亚大陆和北非地区。研究结果如下:在前苏联国家中,俄罗斯的互联网活跃度最高,具有经济发展优势,格鲁吉亚也是如此;在欧亚大陆和北非的一些国家中,阿塞拜疆成为全球变暖下脆弱国家的风险最低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Text Big Data Analytics: Exploring API opportunity: Internet as global storage — how to get the situation awareness from dark data
Text Big Data Analytics Study «Third Wave» is described. Morphological matrix of several Keywords Phrases was collected from Internet's open textual resources using API. The results are analyzed from the point of view that global Internet's audience forms «people-to-IT» system through that we can study the three levels of behaviour of Global society. Level 1 — countries' activity on the Internet. Level 2 — technological evolution in countries. Level 3 — countries' reaction to destructive stress factors. Cluster analysis was used for investigation of Level 1. Simon Wardley's Value Chain Map was used for investigation of Level 2. And diagrams with percentage ratio of different sets of Keywords Phrases were used for investigation of Level 3. Article is focused on regions of Eurasia and North Africa. The Study findings are following: among post-Soviet countries Russia shows the highest activity on Internet and has advantages of economic development, as well as Georgia; Azerbaijan among some countries from Eurasia and North Africa shows the lowest risk to become fragile country under Global warming.
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