On developing extraction rules for mining informal scientific references from Altmetric data sources
View/ Open
Date
2015-06-04Author
Khawaja, Waqas
Taylor, Michael
Davis, Brian
Metadata
Show full item recordUsage
This item's downloads: 464 (view details)
Cited 1 times in Scopus (view citations)
Recommended Citation
Khawaja, Waqas, Taylor, Michael, & Davis, Brian. (2015). On Developing Extraction Rules for Mining Informal Scientific References from Altmetric Data Sources. In Chris Biemann, Siegfried Handschuh, André Freitas, Farid Meziane & Elisabeth Métais (Eds.), Natural Language Processing and Information Systems: 20th International Conference on Applications of Natural Language to Information Systems, NLDB 2015, Passau, Germany, June 17-19, 2015, Proceedings (pp. 443-447). Cham: Springer International Publishing.
Published Version
Abstract
Altmetrics measure scientific impact outside of traditional scientific literature. We identify mentions of scientific research or entities like researchers, academic or research organizations in a corpus containing blogs, articles, news items etc. We first manually analyse the corpus for patterns of such informal mentions and then apply text mining techniques by developing extraction rules for mining informal mentions. We apply them to our development corpus and present our results. This work takes us closer to developing concrete altmetrics for determining research impact on news and public discourse ultimately leading to measuring impact of scientific research on government policies.