Towards the social media studies of science: social media metrics, present and future

In this paper we aim at providing a general reflection around the present and future of social media metrics (or altmetrics) and how they could evolve into a new discipline focused on the study of the relationships and interactions between science and social media, in what could be seen as the social media studies of science.

💡 Research Summary

The paper provides a comprehensive overview of the emergence, current state, and prospective development of social media metrics (SMM), commonly referred to as altmetrics, within the context of scholarly communication and research evaluation. It begins by tracing the origin of altmetrics to the 2010 Altmetric Manifesto, noting that despite rapid adoption, the term suffers from a lack of a precise, universally accepted definition, leading to criticism that it is “a good idea with a bad name.”

SMM differ from traditional citation-based indicators by capturing mentions of scholarly objects—articles, datasets, policy documents, etc.—across a wide array of online platforms such as Twitter, Facebook, blogs, Wikipedia, and others. The authors identify four major challenges that currently limit the reliability and utility of SMM.

First, source heterogeneity and commercial dependence: most data are harvested by commercial aggregators (Altmetric.com, PlumX, Crossref Event Data). These services focus primarily on academic‑centric platforms, often neglecting non‑academic sources such as news media or policy reports, and their proprietary nature hampers transparency, reproducibility, and open access.

Second, coverage imbalance: platforms like Mendeley, which are tightly linked to scholarly workflows, exhibit high coverage and strong correlations with citation counts, whereas broader social platforms (Twitter, Facebook) show low coverage and weak, sometimes inconsistent, correlations. This suggests that SMM may reflect “social attention” rather than scholarly impact.

Third, correlation and evaluative validity: numerous studies cited in the paper demonstrate that Mendeley saves correlate positively with citations, while Twitter mentions, blog posts, or Facebook shares often display modest or even negative relationships. Consequently, the authors argue that SMM capture a distinct dimension of influence—public engagement, diffusion speed, and emotional resonance—that complements but does not replace traditional metrics.

Fourth, theoretical vacuum: existing citation theories (normative, social constructivist) do not adequately explain the dynamics of social media activity. The rapid diffusion, sentiment expression, and network effects characteristic of platforms require new conceptual models that integrate information diffusion theory, social network analysis, and sentiment analysis.

To address these gaps, the paper proposes a research agenda comprising: (1) standardization of data collection and metric definitions; (2) inclusion of non‑academic sources to broaden coverage; (3) development of open‑source aggregation tools to reduce commercial lock‑in; (4) mixed‑methods approaches that combine quantitative counts with qualitative sentiment and network analyses; and (5) comparative studies that account for geographic, cultural, and political variations in social media use (e.g., contrasting Cuban and Spanish Twitter activity).

Building on this agenda, the authors introduce the notion of “Social Media Studies of Science” as a nascent interdisciplinary field. This field would systematically investigate the bidirectional relationships between scientific objects and social media, examine how scholarly communication is perceived and reshaped in public discourse, and assess the role of policy makers, journalists, and the general public in the diffusion of scientific knowledge. It would also explore scholars’ own participation in social media debates, the formation of online scholarly communities, and the impact of platform algorithms on the visibility of research.

Finally, the paper highlights the influence of geopolitical and infrastructural factors—such as internet censorship, economic inequality, and cultural norms—on the accessibility and effectiveness of social media for scientific communication. These structural constraints generate a “altmetric divide” that can exacerbate global disparities in the visibility of research.

In conclusion, while SMM are still in an early, fragmented stage characterized by data quality, standardization, and theoretical challenges, they offer a promising complementary lens for understanding scientific impact beyond citations. The authors argue that, with concerted multidisciplinary collaboration, open‑data policies, and robust methodological frameworks, Social Media Studies of Science can mature into a distinct discipline that enriches both the evaluation of research and the broader societal engagement with science.