Accurately evaluating scholarly influence is essential for fair academic assessment, yet traditional bibliometric indicators - dominated by publication and citation counts - often favor hyperprolific authors over those with deeper, long-term impact. We propose the x-index, a novel citation-based metric that conceptualizes citation as a process of knowledge diffusion and incorporates citation distance to reflect the structural reach of scholarly work. By weighting citations according to the collaborative proximity between citing and cited authors, the x-index captures both the depth and breadth of influence within evolving academic networks. Empirical analyses show that the x-index significantly improves the rankings of Turing Award recipients while reducing those of hyperprolific authors, better aligning rankings with recognized academic merit. It also demonstrates superior discriminatory power among early-career researchers and reveals stronger sensitivity to institutional research quality. These results suggest that the x-index offers a more equitable and forward-looking alternative to existing metrics, with practical applications in talent identification, funding decisions, and academic recommendation systems.

翻译：准确评估学术影响力对于公平的学术评价至关重要，然而传统文献计量指标——以发文量和被引频次为主导——往往更青睐高产作者，而非那些具有更深远、长期影响的学者。我们提出x指数，这是一种新颖的基于引用的度量指标，它将引用概念化为知识扩散的过程，并通过纳入引用距离来反映学术工作的结构性传播范围。通过根据引用作者与被引作者之间的协作邻近度对引用进行加权，x指数能够捕捉学术网络演进过程中影响力的深度与广度。实证分析表明，x指数显著提升了图灵奖获得者的排名，同时降低了高产作者的排名，使排名与公认的学术成就更加吻合。该指标在区分早期职业研究者方面也表现出更优的判别力，并且对机构研究质量显示出更强的敏感性。这些结果表明，x指数为现有指标提供了一个更公平且更具前瞻性的替代方案，在人才识别、资助决策和学术推荐系统中具有实际应用价值。