Co-citations in context: Disciplinary heterogeneity is relevant

Self Cite

Recently, Wu, Wang, and Evans (2019) proposed a new family of indicators, which measure whether a scientific publication is disruptive to a field or tradition of research. Such disruptive influences are characterized by citations to a focal paper, but not its cited references. In this study, we are interested in the question of convergent validity. We used external criteria of newness to examine convergent validity: In the post-publication peer review system of F1000Prime, experts assess papers whether the reported research fulfills these criteria (e.g., reports new findings). This study is based on 120,179 papers from F1000Prime published between 2000 and 2016. In the first part of the study we discuss the indicators. Based on the insights from the discussion, we propose alternate variants of disruption indicators. In the second part, we investigate the convergent validity of the indicators and the (possibly) improved variants. Although the results of a factor analysis show that the different variants measure similar dimensions, the results of regression analyses reveal that one variant ( DI5) performs slightly better than the others.

Section: Indicators Measuring Disruptionmentioning

confidence: 99%

Are disruption index indicators convergently valid? The comparison of several indicator variants with assessments by peers

Bornmann

Devarakonda

Tekles

et al. 2020

Self Cite

“…Novel, atypical, or otherwise unusual combinations of cocited articles have been explored at the journal level (Boyack & Klavans, 2014;Bradley, Devarakonda, et al, 2020;Uzzi, Mukherjee, et al, 2013;Wang, Veugelers, & Stephan, 2017). However, journal-level classifications have limited resolution relative to article-level studies, which may better represent the actual structure and aggregations of the scientific literature (Gómez, Bordons, et al, 1996;Klavans & Boyack, 2017;Milojevic, 2019;Shu, Julien, et al, 2019;Waltman & van Eck, 2012).…”

Section: Introductionmentioning

confidence: 99%

Frequently cocited publications: Features and kinetics

Devarakonda

Bradley

Korobskiy

et al. 2020

Self Cite

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 θ, an a priori estimate of the probability of co-citation between x and y, prior to their first co-citation.Thus, low values for θ 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 θ, 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.

“…In closing, this study primarily concerned examining immunology publications and others connected to them by citation. Other studies have shown that citation behavior can depend significantly on the field (Bradley, Devarakonda, et al, 2020;Wallace, Larivière, & Gingras, 2012), making extrapolation of trends from one field to another premature. Thus, the trends in this study may not be consistently found in other research disciplines or time frames.…”

Section: Discussionmentioning

confidence: 99%

Finding scientific communities in citation graphs: Articles and authors

Chandrasekharan

Zaka

Gallo

et al. 2021

Self Cite

Understanding the nature and organization of scientific communities is of broad interest. The ‘Invisible College’ is a historical metaphor for one such type of community that refers to a small group of scientists working on a problem of common interest. The scientific and social behavior of such colleges has been the subject of case studies that have examined limited samples of the scientific enterprise. We introduce a meta-method for large-scale discovery that consists of a pipeline to select themed article clusters, whose authors can then be analyzed. A sample of article clusters produced by this pipeline was reviewed by experts, who inferred significant thematic relatedness within clusters, suggesting that authors linked to such clusters may represent valid communities of practice. We explore properties of the author communities identified by our pipeline, and the publication and citation practices of both typical and highly influential authors. Our study reveals that popular domain-independent criteria for graphical cluster quality must be carefully interpreted in the context of searching for author communities, and also suggests a role for contextual criteria.