Abstract
Quantitatively measuring the impact-related aspects of scientific, engineering, and technological (SET) innovations is a fundamental problem with broad applications. Traditional citation-based measures for assessing the impact of innovations and related entities do not take into account the content of the publications. This limits their ability to provide rigorous quality-related metrics because they cannot account for the reasons that led to a citation. We present approaches to estimate content-aware bibliometrics to quantitatively measure the scholarly impact of a publication. Our approaches assess the impact of a cited publication by the extent to which the cited publication informs the citing publication. We introduce a new metric, called Content Informed Index (CII), that uses the content of the paper as a source of distant-supervision, to quantify how much the cited-node informs the citing-node. We evaluate the weights estimated by our approach on three manually annotated datasets, where the annotations quantify the extent of information in the citation. Particularly, we evaluate how well the ranking imposed by our approach associates with the ranking imposed by the manual annotations. CII achieves up to 103% improvement in performance as compared to the second-best performing approach.
| Original language | English (US) |
|---|---|
| Title of host publication | EMNLP 2021 - 2021 Conference on Empirical Methods in Natural Language Processing, Proceedings |
| Publisher | Association for Computational Linguistics (ACL) |
| Pages | 6041-6053 |
| Number of pages | 13 |
| ISBN (Electronic) | 9781955917094 |
| DOIs | |
| State | Published - 2021 |
| Event | 2021 Conference on Empirical Methods in Natural Language Processing, EMNLP 2021 - Hybrid, Punta Cana, Dominican Republic Duration: Nov 7 2021 → Nov 11 2021 |
Publication series
| Name | EMNLP 2021 - 2021 Conference on Empirical Methods in Natural Language Processing, Proceedings |
|---|
Conference
| Conference | 2021 Conference on Empirical Methods in Natural Language Processing, EMNLP 2021 |
|---|---|
| Country/Territory | Dominican Republic |
| City | Hybrid, Punta Cana |
| Period | 11/7/21 → 11/11/21 |
Bibliographical note
Funding Information:This work was supported in part by NSF (1447788, 1704074, 1757916, 1834251), Army Research Office (W911NF1810344), and the Digital Technology Center at the University of Minnesota. Access to research and computing facilities was provided by the Digital Technology Center and the Minnesota Supercomputing Institute.
Publisher Copyright:
© 2021 Association for Computational Linguistics
Fingerprint
Dive into the research topics of 'Evaluating Scholarly Impact: Towards Content-Aware Bibliometrics'. Together they form a unique fingerprint.Cite this
- APA
- Standard
- Harvard
- Vancouver
- Author
- BIBTEX
- RIS