Document Type : Research Paper
Authors
1 Department of Knowledge and Information Science, Payame Noor University, Tehran, Iran
2 Department of Physics, Jahrom University, Jahrom, Iran
3 Department of Management, Payame Noor University, Tehran, Iran.
Abstract
Introduction
In recent decades, evaluating the impact of scientific outputs has become a central concern in the fields of scientometrics and knowledge management. Traditional citation-based indicators, such as citation counts, have long been recognized as reliable measures of scholarly impact. However, these indicators suffer from limitations, including time delays in citation accumulation and insufficient coverage of online scholarly interactions. With the rapid development of web technologies and the widespread use of academic social networks, new approaches known as altmetrics have emerged. These metrics provide a more immediate and broader reflection of the attention and usage of scholarly outputs by capturing data from various platforms such as social media, reference management tools, and online repositories. Despite their growing popularity, a key question remains regarding the extent to which altmetrics correlate with and predict traditional citation-based indicators, particularly in specialized fields such as particle physics, where publication and citation behaviors may differ significantly.
Literature Review
A review of previous studies indicates that the relationship between altmetrics and traditional scientometric indicators has attracted considerable scholarly attention in recent years. Many studies report a positive correlation between certain altmetric indicators—such as Mendeley readership—and citation counts. Additionally, evidence suggests that indicators reflecting scholarly engagement, such as saving and downloading, tend to have stronger predictive power than those based on social media activity. However, findings across disciplines are not consistent. In fields such as medical and life sciences, strong correlations between altmetrics and citations have been observed, whereas in other disciplines, these relationships appear weak or statistically insignificant. This inconsistency highlights the influence of contextual factors, including disciplinary norms, communication practices, and the level of adoption of digital tools among researchers. Consequently, domain-specific studies are essential for a more accurate understanding of these relationships.
Methodology
This applied study adopts a descriptive-analytical approach within the framework of altmetrics. The statistical population consists of 5,704 documents in the field of particle physics indexed in the Scopus database between 2000 and 2019. From this population, a sample of 103 highly cited documents was selected based on Scopus classifications. Altmetric data for these documents were extracted from the PlumX platform, covering five main categories: citations, usage, captures, mentions, and social media interactions. In this study, the dependent variable is the number of citations received in Scopus, while the independent variables are the various PlumX metrics. Data analysis was conducted using descriptive statistics, Pearson correlation coefficients to examine relationships between variables, and multiple regression analysis to assess the predictive power of altmetric indicators. All analyses were performed using SPSS software.
Results
The findings reveal that the total number of citations received by the sampled documents in Scopus is 56,861, with an average of approximately 552 citations per document. In PlumX, the total citation count for these documents is 43,278. Among the altmetric dimensions, “captures” (particularly Mendeley readership) and “usage” (such as abstract views in databases) show substantial levels of engagement. Pearson correlation analysis indicates a strong and statistically significant positive relationship between PlumX citations and Scopus citations. Additionally, the “captures” and “mentions” indicators demonstrate significant positive correlations with Scopus citation counts. In contrast, “usage” and “social media” indicators do not exhibit statistically significant relationships with citation counts. The results of multiple regression analysis show that the model has a high explanatory power (R² ≈ 0.93). Within this model, PlumX citations emerge as the strongest predictor of Scopus citations, followed by captures and mentions, while other variables do not significantly contribute to the prediction.
Discussion
The results of this study suggest that not all dimensions of altmetrics equally contribute to predicting scholarly impact. Indicators that reflect actual scholarly engagement such as reading, saving, and citing demonstrate stronger predictive capabilities compared to those based on general social media activity. This pattern may be attributed to the specialized nature of particle physics, where scholarly communication predominantly occurs through formal and discipline-specific channels rather than general social media platforms. Furthermore, the findings are consistent with some previous studies while diverging from others, reinforcing the importance of considering disciplinary characteristics when interpreting altmetric data. Overall, altmetrics appear to function more effectively as complementary tools rather than replacements for traditional citation-based indicators.
Conclusion
In conclusion, the findings indicate that altmetric indicators particularly those related to scholarly usage and citation can play a meaningful role in predicting citation counts in traditional databases such as Scopus. However, social media-based indicators alone are insufficient for predicting scholarly impact and should be used with caution. Therefore, it is recommended that research evaluation frameworks incorporate a combination of traditional and altmetric indicators to achieve a more comprehensive assessment. Additionally, enhancing researchers’ awareness and skills in using altmetric tools may contribute to increasing the visibility and impact of their scholarly work.
Keywords
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