coupling_strength {biblionetwork} | R Documentation |
Calculating the Coupling Strength Measure for Edges
Description
This function calculates the coupling strength measure (following Vladutz and Cook 1984 and Shen et al. 2019)
from a direct citation data frame. It is a refinement of biblio_coupling()
:
it takes into account the frequency with which a reference shared by two articles has been cited in the whole corpus.
In other words, the most cited references are less important in the links between two articles, than references that have
been rarely cited. To a certain extent, it is similar to the tf-idf measure.
Usage
coupling_strength(
dt,
source,
ref,
weight_threshold = 1,
output_in_character = TRUE
)
Arguments
dt |
The data frame with citing and cited documents. |
source |
the column name of the source identifiers, that is the documents that are citing. |
ref |
the column name of the references that are cited. |
weight_threshold |
Corresponds to the value of the non-normalized weights of edges. The function just keeps the edges
that have a non-normalized weight superior to the |
output_in_character |
If TRUE, the function ends by transforming the |
Value
A data.table with the articles identifiers in from
and to
columns, with the coupling strength measure in
another column. It also keeps a copy of from
and to
in the Source
and Target
columns. This is useful is you
are using the tidygraph package then, where from
and to
values are modified when creating a graph.
References
Shen S, Zhu D, Rousseau R, Su X, Wang D (2019).
“A Refined Method for Computing Bibliographic Coupling Strengths.”
Journal of Informetrics, 13(2), 605–615.
https://linkinghub.elsevier.com/retrieve/pii/S1751157716300244.
Vladutz G, Cook J (1984).
“Bibliographic Coupling and Subject Relatedness.”
Proceedings of the American Society for Information Science, 21, 204–207.
Examples
library(biblionetwork)
coupling_strength(Ref_stagflation,
source = "Citing_ItemID_Ref",
ref = "ItemID_Ref")