Authorship, citations, acknowledgments and visibility in social media: Symbolic capital in the multifaceted reward system of science is a research paper published in Social Science Information (2018). On theSindex it has a DataRank of 2.1. It has been cited 89 times, with 80 citing works in its 1-hop citation network.
The reward system of science is undergoing significant changes, as traditional indicators compete with initiatives that offer novel means of disseminating and assessing scholarly impact. This article considers a number of aspects of this reward system, including authorship, citations, acknowledgements and the growing use of social media platforms by academics, with an eye towards identifying contemporary issues relating to scholarly communication practices, as understood through the perspectives of Bourdieu’s symbolic capital and Merton’s recognition framework. The article posits that, while scientific capital remains the foundation upon which the reward system of science is built, this system is revealing itself to be more and more multifaceted, extremely complex, and facing increasing tension between its traditional means of evaluation and the potential of new indicators in the digital era. The article presents an extended literature review, as well as recommendations for further consideration and empirical research. A better understanding of the perceptions of academics would be necessary to properly assess the effects of these new indicators on scholarly communication practices and the reward system of science.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.675
From this paper's citation signal
Citation Network Contribution
1.5
From 49 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 31% comes from its base citations and 69% from the citation network (49 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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