Exploratory Chronotopic Data Analysis

被引:6
|
作者
Adams, Benjamin [1 ]
Gahegan, Mark [1 ]
机构
[1] Univ Auckland, Ctr eRes, Auckland, New Zealand
关键词
Place; Time; Chronology; Historical geographic information science; Big data; Volunteered geographic information; SPACE; TIME; ISSUES;
D O I
10.1007/978-3-319-45738-3_16
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The intrinsic connection between place, space, and time in narrative texts is the subject of chronotopic literary analysis. We take the notion of the chronotope and apply it to exploratory analysis of unstructured big data. Exploratory chronotopic data analysis provides a data-driven perspective on how place, space, and time are connected in large, crowdsourced text collections. In this study, we processed the English Wikipedia text to find all co-occurrences of named places and dates and discovered that times are linked to places in a large majority of cases. We analyzed these millions of connections between places and dates and discovered a number of interesting trends. Because of the scale of the data involved, we suggest that chronotopic data analysis will lead to the development of new data models and methods for geographic information science and related fields, such as digital humanities.
引用
收藏
页码:243 / 258
页数:16
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