A Language-based Approach to Measuring Scholarly Impact

Sean Gerrish · David M. Blei

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scientometrics and bibliometrics research Advanced Text Analysis Techniques Computational and Text Analysis Methods

Abstract

Identifying the most influential documents in a corpus is an important problem in many fields, from information science and historiography to text summarization and news aggregation. Unfortunately, traditional bibliometrics such as citations are often not available. We propose using changes in the thematic content of documents over time to measure the importance of individual documents within the collection. We describe a dynamic topic model for both quantifying and qualifying the impact of these documents. We validate the model by analyzing three large corpora of scientific articles. Our measurement of a document’s impact correlates significantly with its number of citations. 1

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References

1996Bibliometrics, Citation Analysis and Co-Citation Analysis: A Review of Literature I 2008Scientific paper summarization using citation summary networks 2007Unsupervised prediction of citation influences 2008Prediction of citation counts for clinical articles at two years using data available within three weeks of publication: retrospective cohort study

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