Journal article
Topic-based Pagerank: toward a topic-level scientific evaluation
Scientometrics, Vol.100(2), pp.407-437
Aug 2014
Abstract
Within the same research field, different subfields and topics may exhibit varied citation behaviors and scholarly communication patterns. For a more effect scientific evaluation at the topic level, this study proposes a topic-based PageRank approach. This approach aims to evaluate the scientific impact of research entities (e.g., papers, authors, journals, and institutions) at the topic-level. The proposed topic-based PageRank, when applied to a data set on library and information science publications, has effectively detected a variety of research topics and identified authors, papers, and journals of the highest impact from each topic. Evaluation results show that compared with the standard PageRank and a topic modeling technique, the proposed topic-based PageRank has the best performance on relevance and impact. Different perspectives of organizing scientific literature are also discussed and this study recommends the mode of organization that integrates stable research domains and dynamic topics.
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Details
- Title
- Topic-based Pagerank: toward a topic-level scientific evaluation
- Creators
- Erjia Yan - College of Computing and Informatics Drexel University 3141 Chestnut Street Philadelphia PA 19104 USA
- Publication Details
- Scientometrics, Vol.100(2), pp.407-437
- Publisher
- Springer Netherlands; Dordrecht
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Information Science (Informatics)
- Identifiers
- 991014976888104721
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Source: InCites
InCites Highlights
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- Web of Science research areas
- Computer Science, Interdisciplinary Applications
- Information Science & Library Science