DLCLFeb 3, 2025

Originality in scientific titles and abstracts can predict citation count

arXiv:2502.01417v12 citationsh-index: 42
Originality Synthesis-oriented
AI Analysis

This research addresses the problem of predicting scientific impact for researchers and institutions, but it is incremental as it applies an existing measure to a new dataset.

The study applied a computational measure of originality (Divergent Semantic Integration) to 99,557 scientific titles and abstracts, finding a statistically significant positive correlation with citation counts after 5 years, with an adjusted R² of 0.13 across all fields.

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.

Foundations

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