Semantic similarity-based credit attribution on citation paths: a method for allocating residual citation to and investigating depth of influence of scientific communications

• Published in: Scientometrics 2022-11, Vol.127 (11), p.6257-6277
• Main Authors: Asubiaro, Toluwase Victor, Ajiferuke, Isola
• Format: Article
• Language: English
• Subjects: Citation analysis; Computer Science; Information Storage and Retrieval; Library Science; Scholarly communication; Semantics; Similarity
• ISSN: 0138-9130; 1588-2861
• DOI: 10.1007/s11192-022-04522-3

This study proposes a method for assessing the impact of scientific communication on their citation paths beyond conventional direct citations. The proposed method considers the contribution of scientific communication to their nth generation citations as a basis for calculating residual citations. Residual citations that are lost due to citation practices termed “Obliteration by Incorporation” and the “Palimpsestic Syndrome” in consequent citations in the second, third or nth generations are reconstituted. The proposed method is based on the semantic similarity between the citation contexts of a publication and those of its nth generation citations in their n + 1th generation citations. The proposed method was demonstrated using a sample of biomedical publications with ten base articles and their five generations of citations. Like the cascading citation system, residual citations accruing to articles from their generations of citations decreased as the number of generations increased. However, residual citation weights accrued to publications at all generation levels were statistically different between the proposed residual citation and the cascading citation system. This method introduces a new frontier that assesses the depth of impact of a publication (beyond the conventional direct citation level).