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New Technology of Library and Information Service  2016, Vol. 32 Issue (11): 54-63    DOI: 10.11925/infotech.1003-3513.2016.11.07
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Analyzing Online Usage & Sharing of Highly Cited Papers
Kuang Denghui()
Nankai University Library, Tianjin 300071, China
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[Objective] This empirical case study aims to validate the effectiveness of using Altmetrics indicators to identify high quality articles. [Methods] First, we retrieved the online usage and sharing data of highly cited papers published by the PLOS journals from social platforms (i.e., CiteULike, Mendeley and Figshare). Second, we examined relationship between these Altmetrics and SCI citation counts of the target papers. [Results] The correlation coefficient between the SCI citation data and the Altmetrics generated by Mendeley was strong (r = 0.376, p = 0.01). Meanwhile, the other two correlation coefficients were weaker. The online usage data from Mendeley might help us identify high impact literature published by specific journals. [Limitations] This research only investigated a few subjects covered by the PLOS serial journals. More research is needed to check the relationship between Altmetrics and citation counts in other fields. [Conclusions] Online usages & sharing data from CiteULike, Mendeley and Figshare might not be able to effectively identify the high impact literature.

Key wordsHighly cited papers      Online usages      Mendeley      CiteULike      Sharing      Figshare     
Received: 08 July 2016      Published: 20 December 2016

Cite this article:

Kuang Denghui. Analyzing Online Usage & Sharing of Highly Cited Papers. New Technology of Library and Information Service, 2016, 32(11): 54-63.

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