A scientometric review of permafrost research based on textual analysis (1948-2020)

被引:12
|
作者
Bordignon, Frederique [1 ]
机构
[1] Ecole Ponts, Marne La Vallee, France
关键词
Text-mining methods; Scientometrics; Semantic mapping; Lexical analysis; Permafrost; Infrastructure vulnerability; DEGRADATION; SCIENCES;
D O I
10.1007/s11192-020-03747-4
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This article proposes an analysis of research dedicated to permafrost. Its originality is twofold: it covers a corpus (n = 16,249) that has never been reviewed before and also makes use of a methodology based on successive textual analysis processes. With the text-mining of additional corpuses, we produce lists of qualified terms to fine-tune the indexing of the main corpus and isolate relevant terminology dedicated to infrastructure and soil properties. With these enrichments combined with other terminological extractions (such as place names recognition), we reveal the internal structure of permafrost research with the help of visual mapping and easily prove that permafrost research is multidisciplinary and multi-topical The semantic map and the diachronic analysis of terms clusters show that the interest had turned since the 1980s towards the role of climate change but also on China's needs for its highway and railway construction sites. The very strong and growing impact of Chinese research, focused on the Tibetan area, is one of the highlights of our data. Furthermore, we propose a focus on infrastructure vulnerability and use soil properties as a proxy to measure the existing interactions between two distinct research communities. The results suggest that research has mainly focused so far on the feasibility of building on frozen ground and exploiting soils, but remains at an early stage of addressing the impact of global warming on infrastructure degradation and its resilience. This study offers insights to permafrost experts, but also provide a methodology that could be reused for other investigations.
引用
收藏
页码:417 / 436
页数:20
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