# Frequently Co-cited Publications: Features and Kinetics Source: [Frequently Co-cited Publications: Features and Kinetics]() Collection index: [llms.txt]() Data updated: 2025-10-25T23:59:05.045Z Authors: Sitaram Devarakonda, James Bradley, Dmitriy Korobskiy, Tandy Warnow, George Chacko Published: 2020-05-10T21:37:18.000Z ## Abstract Co-citation measurements can reveal the extent to which a concept representing a novel combination of existing ideas evolves towards a specialty. The strength of co-citation is represented by its frequency, which accumulates over time. Of interest is whether underlying features associated with the strength of co-citation can be identified. We use the proximal citation network for a given pair of articles (x, y) to compute theta, an a priori estimate of the probability of co-citation between x and y, prior to their first co-citation.Thus, low values for theta reflect pairs of articles for which co-citation is presumed less likely. We observe that co-citation frequencies are a composite of power-law and lognormal distributions, and that very high co-citation frequencies are more likely to be composed of pairs with low values of theta, reflecting the impact of a novel combination of ideas. Furthermore, we note that the occurrence of a direct citation between two members of a co-cited pair increases with co-citation frequency. Finally, we identify cases of frequently co-cited publications that accumulate co-citations after an extended period of dormancy. ## Recorded benchmark results A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. ## Original sources and implementation [Original paper]() [PDF]()