Journal article
Assessing the impact of software on science: A bootstrapped learning of software entities in full-text papers
Journal of informetrics, v 9(4), pp 860-871
Oct 2015
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
•We propose an improved bootstrapping method to extract software entities from full-text papers.•A positive correlation is found between the number of mentions and the number citations.•Software is widely used in the science community along with a substantial uncitedness.•The 80/20 rule has been found in software mentions and citations.
Although software has helped researchers conduct research, little is known of the impact of software on science. To fill this gap, this article proposes an improved bootstrapping method to extract software entities from full-text papers and assess their impact on science. Evaluation results show that the proposed entity extraction system outperforms three baseline methods on extracting software entities from full-text papers. The proposed method is then used to learn software entities from all papers published in PLoS ONE in 2014. More than 2000 unique software entities are obtained which accounted for more than 20,000 mentions and more than 7000 citations. The paper finds that software is commonly used in the scientific community along with a substantial uncitedness.
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Details
- Title
- Assessing the impact of software on science: A bootstrapped learning of software entities in full-text papers
- Creators
- Xuelian Pan - School of Information Management, Nanjing University, Nanjing, ChinaErjia Yan - College of Computing and Informatics, Drexel University, Philadelphia, USAQianqian Wang - College of Humanities, Jinling Institute of Technology, Nanjing, ChinaWeina Hua - School of Information Management, Nanjing University, Nanjing, China
- Publication Details
- Journal of informetrics, v 9(4), pp 860-871
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000367612600014
- Scopus ID
- 2-s2.0-84941268953
- Other Identifier
- 991014976883604721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Computer Science, Interdisciplinary Applications
- Information Science & Library Science