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Source Inflibnet's Institutional Repository
Content type Text
Publisher INFLIBNET Centre
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science ♦ Library & information sciences
Subject Keyword Altmetrics ♦ Research Impact ♦ Research Evaluation ♦ Citation Forecast
Abstract Research output is multidimensional in nature and the existing bibliometric tools fail to cope up with the growing scope of the research output forms and also have citations as their sole base to evaluate research impact. Citations indicate the usage of a particular research work formally which reflect only the impact among the research community while societal impact is totally ignored. Altmetrics tracks heterogeneous research usages in the online environment which brings impact beyond academia in the picture. Bibliometrics and altmetrics complement each other in creating a more meaningful research evaluationmetric. Thus, the missing parts of citations in evaluating research impact like time consuming and fewothers are expected to be compensated to an extent.With this aim, the paper discusses the limitations of the existing indicators and how altmetrics can be used to fill few gaps. Sample data fromPLOS ONE journal was collected on Brain Damage during 2008-09 to prove that article downloads cannot be potentially used for predicting citations. It was also found that citations and altmetrics do not correlate as they measure different research impacts. The paper argues that citation counts highlights the work that was used to create knowledge and altmetrics reflects if the created knowledge was used for the betterment of the society. Therefore, this paper also strongly concludes that altmetrics cannot be used to predict citations and also states that either altmetrics or bibliometrics will remain unsolved puzzle in evaluating research output unless they are combined together as far as the evaluation metrics is concerned.
ISBN 9789381232057
Education Level UG and PG
Learning Resource Type Article