This invention discloses a method and
system for quantitatively assessing
citation impact through sentiment semantic deconstruction, relating to the field of text analysis technology. The method includes: constructing a feature word
score table; performing dependency
parsing on the cited
sentence to obtain a part-of-speech position
feature set, segmenting the cited
sentence, obtaining multiple cited clauses, removing non-evaluative feature words, and obtaining multiple optimized clauses; identifying the subject scores of the multiple optimized clauses and obtaining multiple subject
score identification results; identifying the auxiliary word scores of the multiple optimized clauses and obtaining multiple auxiliary word
score identification results; obtaining the score of each optimized clause and calculating the quantitative score of
citation impact. This invention solves the technical problem in existing technologies where
citation sentiment analysis only reaches a coarse-grained classification of positive, negative, and neutral, making it difficult to quantitatively assess the degree of citation
impact. It achieves the technical effect of transforming qualitative citation
impact evaluation into standardized quantitative scoring, improving the objectivity and comparability of the assessment.