This study explores weighted author co-citation analysis (ACA) through a comparison of results from four weighted citation counting methods. The data set used comprises full-text research articles published in four top-tier library and information science (LIS) journals from 2011 to 2018. It finds that in-text frequency-weighted counting performs as well as traditional counting in identifying major dimensions of the LIS field but also shows more detail. Re-citation-based counting appears to highlight well-integrated specialties and weaken the presence of more fragmented ones compared to traditional counting. In-text frequency weighted re-citation counting, expected to highlight “deep” impact, appears to effectively zoom into the field to show intense streams of research within it, but fail to identify major dimensions of the field, essentially providing a telescopic view of the LIS field instead of the panoramic one that the other three methods provide. Measuring deep impact may be interesting and important for research evaluation but fails to retain the broader context that makes the visualizations of research fields so informative. It appears that what may be “noise” when considering impact of individuals can provide the context that allows us to see the forest for the trees when examining intellectual structures of research fields as in the case of traditional ACA.
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Python regular expressions for identifying in-text citations and their components.
# In-text reference publication year, possibly plus disambiguating lower case letter:
pubyearRE = r'(?:\d\d[a-z]?)'
# Multiple publication years (for the same authors):
pubyearsRE = r'(?:(?:' + pubyearRE + ',\s +)*' + pubyearRE + r')'
# Page numbers within an intext reference (to be recognized but ignored):
pageRE = r'(?:\bpp?\.\s + (\d +|[iIvVxXlLdDmM] +)(?:[-](\d +|[iIvVxXlLdDmM] +))?)'
# Possible introductory phrase within reference block parentheses (to be recognized but ignored):
egRE = r'(?:e[.]g[.],?\s +)?'
# Frequent name prefixes that may appear in lower-case in an author name:
namePrefixRE = r"(?:al|da|dal|dalle|de|del|della|den|der|des|det|el|van|von|y|zu|zum|zur)"
# A name component is a series of capitalized words possibly prefixed by a lower-case prefix:
nameComponentRE = r'(?:' + namePrefixRE + r"\s +)*(?:(?:[dtlO]')?[A-Z]\w*)"
# A full last name is composed of name components separated by hyphens:
nameRE = r'(?:' + nameComponentRE + r'(?:(\s +|-)' + nameComponentRE + r')*)'
# Author names (one or more) flowing with the text:
namesREintext = r'((((((' + nameRE + r'\s +)|((?:' + nameRE + r',\s +) +))and\s +)?)' + nameRE + r')|(' + nameRE + r',?\s + et\s + al\.))'
# Full reference flowing in the text – authors, years, pages:
refREintext = r'(\s + ' + namesREintext + r"([']s)?" + r'\s + \(' + pubyearsRE + r'(?:,\s + ' + pageRE + r')?\))'
# Author names in a parenthetic citation block:
namesREinpar = r'(((?:(?:' + nameRE + r'|(?:' + nameRE + r',\s +)*)\s*(\&|and)\s +)*' + nameRE + r')|(' + nameRE + r',?\s + et\s + al\.))'
# individual reference formats for first and for subsequent reference within a citation block:
refREinpar = r'(' + namesREinpar + r',\s + ' + pubyearsRE + r'(?:,\s + ' + pageRE + r')?)'
refREinpar2 = r'((?:' + namesREinpar + r',\s +)?' + pubyearsRE + r'(?:,\s + ' + pageRE + r')?)'
# Complete reference block enclosed in parentheses:
refsREwithpar = r'(\(' + egRE + refREinpar + r'(?:;\s + ' + refREinpar2 + r')*\))'.
# The full regular expression for the two types of in-text references – separated by parentheses or flowing with the text:
refsRE = r'(' + refREintext + r'|' + refsREwithpar + r')'
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Zhao, D., Strotmann, A. Telescopic and panoramic views of library and information science research 2011–2018: a comparison of four weighting schemes for author co-citation analysis. Scientometrics 124, 255–270 (2020). https://doi.org/10.1007/s11192-020-03462-0
- Weighted citation analysis
- Author co-citation analysis
- Intellectual structure
- Library and information science