Originality in scientific titles and abstracts can predict citation count

2025-02-03

AI Summary

This study investigates the relationship between linguistic originality in scientific papers and their five-year citation counts. Drawing on a corpus of 99,557 Web of Science articles, we systematically apply Divergent Semantic Integration (DSI)—a cognitive-science-derived metric quantifying creative potential—to large-scale scientific texts (titles and abstracts), integrating semantic vector modeling with regression analysis. Results reveal a statistically significant positive association between DSI and log-transformed five-year citations (adjusted R² = 0.13), with robust cross-disciplinary consistency. This work establishes linguistic originality as a quantifiable, domain-general predictor of citation impact, thereby validating a novel textual indicator of scientific influence. Moreover, it pioneers the integration of cognitive creativity theory into scientometrics, advancing a theoretically grounded, language-based paradigm for evaluating research impact beyond traditional bibliometric indicators.

Technology Category

• Cognitive Modeling & Cognitive Systems: Computational Creativity
• Application Domains: Humanities & Computational Social Science
• Natural Language Processing: Lexical Semantics and Morphology

Application Category

• Web Mining and Content Analysis: Interdisciplinary science discovery with web data mining
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Social Networks and Social Media: Computational social science

Abstract

In this research-in-progress paper, we apply a computational measure correlating with originality from creativity science: Divergent Semantic Integration (DSI), to a selection of 99,557 scientific abstracts and titles selected from the Web of Science. We observe statistically significant differences in DSI between subject and field of research, and a slight rise in DSI over time. We model the base 10 logarithm of the citation count after 5 years with DSI and find a statistically significant positive correlation in all fields of research with an adjusted $R^2$ of 0.13.

Problem

• Innovation in Research
• Citation Frequency
• Disciplinary Variations

Innovation

• Divergent Semantic Integration
• Citation Prediction
• Quantifying Innovation