citationsdepends

Citationsdepends is a term used in bibliometrics to describe the phenomenon that citation patterns are influenced by a network of interrelated factors rather than reflecting a simple, intrinsic merit of a single work. It emphasizes that citation counts can be shaped by field size, author and institutional networks, venue prestige, publication age, and practices such as self-citation or preferential citing within subfields.

The concept points to several mechanisms that generate dependencies among citations. Preferential attachment can cause already-cited papers to attract more citations, while clustering within subfields and collaborative networks can amplify local citation rates. Editorial policies, citation behaviors, and cross-disciplinary linkages further modulate how often papers are cited. As a result, raw citation counts may misrepresent relative impact if these dependencies are not accounted for.

Applications and implications include the design of fairer metrics and the need for normalization when comparing papers, authors, or institutions across disciplines and time. Researchers use dependency-aware methods such as mixed-effects models, network-based metrics, and causal inference approaches to better separate genuine impact from structural biases in citation data.

Measurement approaches typically involve modeling citation counts with controls for venue, field, year, and author effects; constructing citation or collaboration networks; and evaluating how citation probabilities change with network position or subfield characteristics.

Limitations include challenges in accurately estimating dependencies, data requirements, and the risk of overadjustment that may obscure real signals. The term remains one of several conceptual tools in bibliometrics for understanding and mitigating biases in citation-based assessments.

See also: bibliometrics, citation analysis, normalization, impact factor, altmetrics, network science.