Altmetrics – A Collated Adjunct Beyond Citations for Scholarly Impact: A Systematic Review
Introduction: In emerging figures, scholars are unifying social media tools like blogs, Twitter, and Mendeley into their professional communications. The online, open nature of these tools reveals the scholarly action to be clear and unambiguous. Metrics which is set on these activities could en...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
JCDR Research and Publications Private Limited
2017-06-01
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| Series: | Journal of Clinical and Diagnostic Research |
| Subjects: | |
| Online Access: | https://jcdr.net/articles/PDF/10078/26153_CE(RA1)_F(T)_PF1(RU_VT_RB)_PFA(P_RB).pdf |
| Summary: | Introduction: In emerging figures, scholars are unifying
social media tools like blogs, Twitter, and Mendeley into their
professional communications. The online, open nature of these
tools reveals the scholarly action to be clear and unambiguous.
Metrics which is set on these activities could enlighten broader,
faster measures of impact, supplementing traditional citation
metrics.
Aim: The present review aims to analyse the correlation of
altmetrics with the traditional citations in medical research.
Materials and Methods: The search strategy used a combination
of controlled vocabulary and free text terms. The main database
searched were PubMed, PubMed Central, Cochrane Review,
Embase and Google Scholar from 2010 to 2016. Out of the total
78 titles appeared seven articles fulfilled the criteria and were
selected for the review.
Results: The positive correlation between altmetrics and
traditional citations indicates that the two are not entirely different
from each other and are familiar with each other. Altmetrics are
usually accessible earlier and enable us to evaluate the social
impact of scholarly research, almost at the actual time.
Conclusion: Much work is needed to develop this research
which will focus on the clarity of the impact signal. Thus newer
dimensions, such as altmetrics and article-level metrics are an
effort to explore the influence of research across the worldwide
population. |
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| ISSN: | 2249-782X 0973-709X |