Citation Farming on ResearchGate: Blatant and Effective
For the research community and platform operators, this work exposes a novel form of citation manipulation on a major academic social network, demonstrating its prevalence and impact.
The study identifies and characterizes citation farming on ResearchGate by analyzing nearly 3000 papers from suspected boosting-service accounts, finding that many papers exhibit equal reference groups—a structural signal of coordinated boosting—and that a substantial share of citations for some authors originates from these suspicious groups.
We investigate platform-native citation farming on ResearchGate by analyzing almost 3000 papers uploaded by five suspected boosting-service provider accounts. From the uploaded papers and associated metadata, we construct both paper-level and author-level citation networks. We introduce an interpretable structural signal for coordinated boosting, equal references groups: clusters of papers with equal reference lists. We find that many papers from our collection exhibit this motif, that is, they disproportionately cite a small set of authors, consistent with coordinated or automated boosting rather than independent scholarly practice. Finally, we show that for some authors in our dataset a substantial share of their citations can be attributed to these suspicious groups. A different citation network was used to validate the rareness of such motifs in legitimate scientific work.