Disciplinary differences in altmetrics for social sciences
Purpose - The purpose of this paper is to contribute to the understanding of altmetrics in different disciplines of Social Science, first, by investigating the current richness and future potential of altmetrics in the selected social science disciplines and then, by evaluating the validity of altme...
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| Main Authors: | , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
2017
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/81432 http://hdl.handle.net/10220/42249 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | Purpose - The purpose of this paper is to contribute to the understanding of altmetrics in different disciplines of Social Science, first, by investigating the current richness and future potential of altmetrics in the selected social science disciplines and then, by evaluating the validity of altmetrics as indicators of research impact in each discipline through correlation analysis.
Design/methodology/approach – This study uses 3 methods to understand the current richness and future potential of 10 altmetric measures in 9 selected disciplines: (1) investigate the distribution and trend of altmetric data, (2) verify the relationship between citation rate and altmetric presence of the discipline using Pearson correlation, and (3) perform word frequency analysis on tweets to understand different altmetric presence in different disciplines. In addition, this study uses Spearman and Sign Test to find the correlation between altmetrics and citation counts for the articles that receive altmetric mention(s) to test the validity of altmetrics as indicators of research impact.
Findings – (1) There is a steady increase in the number of articles that receive altmetric mentions in all disciplines studied. (2) In general, disciplines with higher citation rates have higher altmetric presence. At the same time, altmetrics are also an effective complement to citation in disciplines with low citation rates. (3) There are a moderate correlation with Mendeley and significant but weak correlations with Tweets and CiteULike in 7 disciplines. (4) Altmetrics are most effective as a predictor of citation counts in Psychiatry, Clinical Psychology and Political Science; appear useful in Nursing and Information Science & Library Science; fairly applicable in Health Policy and Services and Management. However, there is low altmetric presence and lack of correlation with citation counts in Business-Finance and Law disciplines.
Originality/value – This paper furthers our understanding of altmetrics in social science disciplines. It reveals the disciplines where altmetrics are most effective, potentially useful and fairly applicable. In addition, it presents evidence that altmetrics are an effective complement to citation in disciplines with low citation rates. |
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