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Building updated research agenda by investigating papers indexed on Google scholar: A natural language processing approach
Author(s)
Date Issued
2020
ISBN
9783030513276
9783030513283
Citation
In Tareq, Ahram (ed.) (2020). Advances in artificial intelligence, software and systems engineering, proceedings of the AHFE 2020 virtual conferences on software and systems engineering, and artificial intelligence and social computing (pp. 298-305).
Type
Conference Paper
Abstract
Under many circumstances, scholars need to identify new research directions by going through many different databases to identify the research gap and identify areas which have not yet been studied thus far. Checking all the electronic databases is tiresome, and one often misses the important pieces. In this paper, we propose to shorten the time required for identifying the research gap by using web scraping and natural language processing. We tested this approach by reviewing three distinct areas: (i) safety awareness, (ii) housing price, (iii) sentiment and artificial intelligence from 1988 to 2019. Tokenisation was used to parse the titles of the publications indexed on Google Scholar. We then ranked the collocations from the highest to the lowest frequency. Thus, we determined the sets of keywords that had not been stated in the title and identified the initial idea as a research void.
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