Assessing the impact of software on science: A bootstrapped learning of software entities in full-text papers

作者：Pan, Xuelian; Yan, Erjia^*; Wang, Qianqian; Hua, Weina

来源：Journal of Informetrics, 2015, 9(4): 860-871.

DOI：10.1016/j.joi.2015.07.012

• Entity extraction
• Information extraction
• Software
• Software citation
• Citation analysis
• Bootstrapping

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.

• 出版日期2015-10
• 单位金陵科技学院; 南京大学