Hongkan Chen

Hongkan Chen, Lutz Bornmann, Yi Bu

The temporal dimension of citation accumulation poses fundamental challenges for quantitative research evaluations, particularly in assessing disruptive and consolidating research through the disruption index (D). While prior studies emphasize minimum citation windows (mostly 3-5 years) for reliable citation impact measurements, the time-sensitive nature of D - which quantifies a paper' s capacity to eclipse prior knowledge - remains underexplored. This study addresses two critical gaps: (1) determining the temporal thresholds required for publications to meet citation/reference prerequisites, and (2) identifying "optimal" citation windows that balance early predictability and longitudinal validity. By analyzing millions of publications across four fields with varying citation dynamics, we employ some metrics to track D stabilization patterns. Key findings reveal that a 10-year window achieves >80% agreement with final D classifications, while shorter windows (3 years) exhibit instability. Publications with >=30 references stabilize 1-3 years faster, and extreme cases (top/bottom 5% D values) become identifiable within 5 years - enabling early detection of 60-80% of highly disruptive and consolidating works. The findings offer significant implications for scholarly evaluation and science policy, emphasizing the need for careful consideration of citation window length in research assessment (based on D).

Hongkan Chen, Qingshan Zhou, Robin Haunschild et al.

In modern scientific collaboration networks, certain researchers play a pivotal role in bridging scholars who have never worked together - a phenomenon we term academic "match-makers." Despite their potential importance, the prevalence, characteristics, benefits, and long-term trajectory of these individuals remain underexplored. Using the Microsoft Academic Graph (MAG), we operationalized a match-maker as an author who, in a given publication, introduced a first-time collaboration between two co-authors, each of whom had previously collaborated with the match-maker but not with each other. We employed a configuration null model to distinguish observed patterns from random chance. Our findings reveal that the match-maker phenomenon is deliberate, prevalent, and consequential. Among authors with over 20 publications, nearly 30% have served as a match-maker, and the probability of acting as one increased eightfold from 1980 to 2019. Publications involving a match-maker are more likely to appear in high-impact journals and exhibit higher disruptiveness - particularly in larger teams - suggesting that match-makers help facilitate what we term integrative disruption. Match-makers tend to emerge early in their careers, peaking around the 20th publication and at an academic age of roughly ten years. While nearly all match-makers eventually experience "abandonment" in the sense that the connected researchers later collaborate without them, their continued involvement remains substantial and is driven by research needs rather than structural factors. This reframes abandonment not as exclusion but as a natural evolution within project-based collaborations. The academic match-maker phenomenon is a strategic feature of collaboration networks characterized by early-career emergence, context-dependent persistence, and tangible contributions to high-impact, disruptive research.

Jinchang Liu, Qingshan Zhou, Hongkan Chen et al.

Science advances not only by accumulating discovered patterns but by changing how new problems and solutions are expressed. While structural indicators track scholarly attention, they offer only an indirect proxy for the reorganization of meaning. We propose a semantic geometry based on the R-P-C (references, focal publication, and citing publications) framework to quantify how a publication positions itself relative to its knowledge base and diffusion. This geometry identifies three publication types: consolidating, exploratory and balanced. Our results show that the semantic similarity and distance between a publication's knowledge base and diffusion serve as a mechanistic explanation for disruption, with novelty (atypical reference combinations) acting as an antecedent disturbance that triggers a semantic rupture. This is related to team size, where small teams preserve a higher potential for exploratory departures while large collaborations systematically align with paradigmatic consolidation. Crucially, this geometry explains why citation trajectories differ; consolidating research earns rapid recognition by lowering comprehension costs, while exploratory work faces high paradigm conversion costs that result in slower, more selective diffusion. Collectively, this R-P-C framework provides a robust instrument for monitoring the dynamic of scientific paradigms.