A comparison of on-line computer science citation databases

  • Authors:

  • Vaclav Petricek;Ingemar J. Cox;Hui Han;Isaac G. Councill;C. Lee Giles

  • Affiliations:

  • University College London, London, United Kingdom;University College London, London, United Kingdom;Yahoo! Inc., Sunnyvale, CA;The School of Information Sciences and Technology, The Pennsylvania State University, University Park, PA;The School of Information Sciences and Technology, The Pennsylvania State University, University Park, PA

  • Venue:
  • ECDL'05 Proceedings of the 9th European conference on Research and Advanced Technology for Digital Libraries
  • Year:
  • 2005

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Abstract

This paper examines the difference and similarities between the two on-line computer science citation databases DBLP and CiteSeer. The database entries in DBLP are inserted manually while the CiteSeer entries are obtained autonomously via a crawl of the Web and automatic processing of user submissions. CiteSeer's autonomous citation database can be considered a form of self-selected on-line survey. It is important to understand the limitations of such databases, particularly when citation information is used to assess the performance of authors, institutions and funding bodies. We show that the CiteSeer database contains considerably fewer single author papers. This bias can be modeled by an exponential process with intuitive explanation. The model permits us to predict that the DBLP database covers approximately 24% of the entire literature of Computer Science. CiteSeer is also biased against low-cited papers. Despite their difference, both databases exhibit similar and significantly different citation distributions compared with previous analysis of the Physics community. In both databases, we also observe that the number of authors per paper has been increasing over time.