Capturing waste recycling science
Gaizka Garechana,
Rosa Rio-Belver,
Ernesto Cilleruelo and
Javier Gavilanes-Trapote
Technological Forecasting and Social Change, 2014, vol. 81, issue C, 250-258
Abstract:
Many institutions from the public and private sector are interested in the characterization of the research taking place in waste recycling (WR) science. Tech mining analysis can be applied to scientific databases with this purpose in mind, but difficulties do arise when designing the search strategy to effectively capture this multidisciplinary area. This paper introduces the process followed to build a query system that aims to solve this problem. This system has been applied to a selection of scientific databases, and the steps followed to download and clean the data are detailed. Initial results are explained, indicating the relevance of each database and quantifying the overlap among them. The main subjects behind the retrieved data have been identified, namely, chemistry, biology and environmental sciences. A precision test conducted by random sampling indicated that, with a confidence level of 95%, the proportion of WR articles is between 74.2 and 79.2% of the retrieved items, while recall is expected to be high, according to available classifications. These results are deemed to be satisfactory enough for basing forthcoming tech mining analyses on this query system.
Keywords: Tech mining; Search strategies; Waste recycling; Bibliometric analysis (search for similar items in EconPapers)
Date: 2014
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0040162512001746
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:81:y:2014:i:c:p:250-258
DOI: 10.1016/j.techfore.2012.07.005
Access Statistics for this article
Technological Forecasting and Social Change is currently edited by Fred Phillips
More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().