An extensive analysis of the presence of altmetric data for Web of Science publications across subject fields and research topics

Abstract

Sufficient data presence is one of the key preconditions for applying metrics in practice. Based on both Altmetric.com data and Mendeley data collected up to 2019, this paper presents a state-of-the-art analysis of the presence of 12 kinds of altmetric events for nearly 12.3 million Web of Science publications published between 2012 and 2018. Results show that even though an upward trend of data presence can be observed over time, except for Mendeley readers and Twitter mentions, the overall presence of most altmetric data is still low. The majority of altmetric events go to publications in the fields of Biomedical and Health Sciences, Social Sciences and Humanities, and Life and Earth Sciences. As to research topics, the level of attention received by research topics varies across altmetric data, and specific altmetric data show different preferences for research topics, on the basis of which a framework for identifying hot research topics is proposed and applied to detect research topics with higher levels of attention garnered on certain altmetric data source. Twitter mentions and policy document citations were selected as two examples to identify hot research topics of interest of Twitter users and policy-makers, respectively, shedding light on the potential of altmetric data in monitoring research trends of specific social attention.

Keywords: Altmetrics; Data coverage; Data intensity; Hot topics; Social attention; Social media metrics.

Fig. 1

Five main subject fields of science of the CWTS classification system. Each circle represents a micro-level field (micro-topics) of clustered publications based on direct citation relations

Fig. 2

The presence of altmetric data and citations over the publication years

Fig. 3

The presence of altmetric data and citations of scientific publications across five subject fields

Fig. 4

Spearman correlation analyses of coverage (upper-right triangle) and intensity (bottom-left triangle) among citations and 12 types of altmetric data at the micro-topic level. WoS citations (CT), Mendeley readers (MR), Twitter mentions (TW), Facebook mentions (FB), news mentions (NS), blogs citations (BL), Reddit mentions (RD), Wikipedia citations (WK), F1000Prime recommendations (FP), video comments (VD), policy document citations (PD), peer review comments (PR), Q&A mentions (QA)

Fig. 5

Two-dimensional system for classifying research topics with different levels of attention

Fig. 6

a The distribution of micro-topics with different levels of attention received on Twitter; and hot research topics mentioned on Twitter in b SSH; c BHS; d PSE; e LES; f MCS

Fig. 7

a The distribution of micro-topics with different levels of attention received in policy documents; and hot research topics cited by policy documents in b SSH; c BHS; d PSE; e LES; f MCS

Fig. 8

Distribution of 12 types of altmetric data and citations of sample publications

Fig. 9

Spearman correlations among coverage (C), density (D), and intensity (I) at the micro-topic level

Fig. 10

Spearman correlation analyses of coverage (upper-right triangle) and intensity (bottom-left triangle) among citations and 12 types of altmetric data at the micro-topic level (with mutual zero-value micro-topics excluded). WoS citations (CT), Mendeley readers (MR), Twitter mentions (TW), Facebook mentions (FB), news mentions (NS), blogs citations (BL), Reddit mentions (RD), Wikipedia citations (WK), F1000Prime recommendations (FP), video comments (VD), policy document citations (PD), peer review comments (PR), Q&A mentions (QA)