Making Big Data Small: Strategies to Expand Urban and Geographical Research Using Social Media

被引:36
作者
Poorthuis, Ate [1 ]
Zook, Matthew [2 ]
机构
[1] Singapore Univ Technol & Design, Humanities Arts & Social Sci, Singapore, Singapore
[2] Univ Kentucky, Informat & Econ Geog, Lexington, KY USA
关键词
Big data; social media; data mining; social science methods; twitter; data frameworks; TWITTER; SYSTEM;
D O I
10.1080/10630732.2017.1335153
中图分类号
TU98 [区域规划、城乡规划];
学科分类号
0814 ; 082803 ; 0833 ;
摘要
While exciting, Big Data (particularly geotagged social media data) has proven difficult for many urbanists and social science researchers to use. As a partial solution, we propose a strategy that enables the fast extracting of only relevant data from large sets of geosocial data. While contrary to many Big Data approachesin which analysis is done on the entire datasetmuch productive social science work can use smaller datasetsaround the same size as census or survey datawithin standard methodological frameworks. The approach we outline in this paperincluding the example of a fully operating systemoffers a solution for urban researchers interested in these types of data but reluctant to personally build data science skills.
引用
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页码:115 / 135
页数:21
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