normalizeCitationScore: Calculate the normalized citation score metric

View source: R/normalizeCItationScore.R

normalizeCitationScoreR Documentation

Calculate the normalized citation score metric

Description

It calculates the normalized citation score for documents, authors and sources using both global and local citations.

Usage

normalizeCitationScore(M, field = "documents", impact.measure = "local")

Arguments

M

is a bibliographic data frame obtained by convert2df function.

field

is a character. It indicates the unit of analysis on which calculate the NCS. It can be equal to field = c("documents", "authors", "sources"). Default is field = "documents".

impact.measure

is a character. It indicates the impact measure used to rank cluster elements (documents, authors or sources). It can be impact.measure = c("local", "global").\ With impact.measure = "local", normalizeCitationScore calculates elements impact using the Normalized Local Citation Score while using impact.measure = "global", the function uses the Normalized Global Citation Score to measure elements impact.

Details

The document Normalized Citation Score (NCS) of a document is calculated by dividing the actual count of citing items by the expected citation rate for documents with the same year of publication.

The MNCS of a set of documents, for example the collected works of an individual, or published on a journal, is the average of the NCS values for all the documents in the set.

The NGCS is the NCS calculated using the global citations (total citations that a document received considering the whole bibliographic database).

The NLCS is the NCS calculated using the local citations (total citations that a document received from a set of documents included in the same collection).

Value

a dataframe.

Examples


## Not run: 
data(management, package = "bibliometrixData")
NCS <- normalizeCitationScore(management, field = "authors", impact.measure = "local")

## End(Not run)


massimoaria/bibliometrix documentation built on April 24, 2024, 8:02 p.m.