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The process of finding out the frequency of citations for various journals or articles or research papers is known as citation analysis. The impact of any research paper can be found by computing the number of citations, the particular journal or paper received. Many researchers quote concepts or ideas from various papers and the final outcome of the paper in their discussion. But it does not always mean that all the authors and papers referred to would be criticizing the referred paper with positive words. Sometimes if the referring paper has produced good results when compared to the referred paper then obviously the authors do not give much positive comments in their discussion. In order to address this problem, we propose the sentiment analysis can be performed to rate the citations based on the polarity level. The sentence parser can be used to identify the adjectives what the authors used in their discussion about the cited paper. Then the identified adjectives can be assigned a score to distinguish it from positive and negative. In between, if any paper is found without clearly mentioning the cited paper with identifiable adjective terms then in can be named as unknown or neutral. The citations can be ranked based on the computed polarity score. The ranking process helps to project the citations which have cited with higher positivity content in their discussion.
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Stored only when both papers are in the corpus — 16 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.