Purpose and Polarity of Citation: Towards NLP-based Bibliometrics
Amjad Abu-Jbara, Jefferson Ezra and Dragomir Radev
Bibliometric measures are commonly used to estimate the popularity and
the impact of published research. Existing bibliometric measures
provide "quantitative" indicators of how good a published paper is.
This does not necessarily reflect the "quality" of the work
presented in the paper. For example, when h-index is computed
for a researcher, all incoming citations are treated equally, ignoring
the fact that some of these citations might be negative. In this
paper, we propose using NLP to add a ``qualitative'' aspect to
biblometrics. We analyze the text that accompanies citations in
scientific articles (which we term citation context). We
propose supervised methods for identifying citation text and analyzing
it to determine the purpose (i.e. author intention) and the polarity
(i.e. author sentiment) of citation.
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