Deriving the impact of scientific publications by mining citation opinion terms

One of the most important measures for estimating the impact of scientific publications is the number of citations they have received. To day, there exist several tools and metrics to evaluate the relative importance of individual papers and publication venues based on their citation distribution. Despite their acknowledged usefulness, most of the existing techniques rely on quantitative rather than qualitative aspects of the citation analysis and thus they are inherently limited in conveying any specific information about the author opinions to wards the papers they cite. In this paper, we introduce a method that combines text mining and lexical analysis in order to elucidate the authors' attitude towards the works they cite in their publications. We have applied our method on a set of 4,520 citations that span to 40 publications and tried to shed some light on the following issues. How often authors express an opinion about the papers they cite? Do all authors who cite the same publication share a common understanding on that publication's impact? Does the citations' context influence people's perception of the referred papers and how we can take context into consideration? Can we define a qualitative measure for esti mating the impact of scientific publications? Our evaluation shows that although authors do not always express their personal opinions about the papers they cite, their judgments (when articulated) have a great influence on the papers' perceived importance.