Public Attention on Research Publications of University of Ruhuna: An Alternative Metric Analysis.

Abstract

Attention towards online access to scholarly publications has been dramatically increased during last two decades among various scholars and professionals. Publishing of articles in online resources has also been highly increased. Research institutions and universities are encouraging their professionals to publish more in internationally recognized online publishers as the citation count can impact on the standards of the institution. The evaluation of scholarly publication and impact measures are completed with several quantitative and qualitative methods. The purpose of the study is to measure and analyze the online impact of articles published by the University of Ruhuna (UoR) in Scopus database during 2012-2017. Citation count was used as the filtering tool and 100 articles were selected from 697 publications of Scopus database. The PlumX metrics with five different categories of data (usage, captures, mentions, social media and citation metrics) were separately collected as alternative metric for data collection on 24.08.2017. Among the results, top ten articles from the top ten subjects were used for analysis. As a result, 697 publications were cited in Scopus database and highest number of articles appeared for physics, medicine and agriculture. Physics and medicine exhibited a strong Pearson’s correlation (r=0.981, P=0.003/r= 0.998, P=0.036) with citation count and social media. Articles of medicine resulted a higher PlumX metrics with all metric types by online interaction. Scopus and CrossRef citation counts represented similar citations for selected publications. The study concludes that, University of Ruhuna has published a quite higher number of publications among other universities in Sri Lanka. Physics, medicine and agriculture related subjects were highly appeared in publications. Topics related to health gathered more attentions in online communities. This study confirmed that, CrossRef DOI aggregation of publications were relevant to prediction of article citation counts.