---
title: "Modern Citation Indicators"
output: rmarkdown::html_vignette
vignette: >
%\VignetteIndexEntry{Modern Citation Indicators}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
resource_files:
- figures/logo.svg
- figures/logo-dark.svg
---
[](https://github.com/CTTIR/scimapR/actions/workflows/R-CMD-check.yaml)
[](https://cttir.github.io/scimapR/)
[](https://CRAN.R-project.org/package=scimapR)
[](https://app.codecov.io/gh/CTTIR/scimapR?branch=main)
[](https://cran.r-project.org/package=scimapR)
[](https://cran.r-project.org/package=scimapR)
[](https://opensource.org/licenses/MIT)
[](https://lifecycle.r-lib.org/articles/stages.html#experimental)
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
```
## Beyond the h-index
scimapR implements several modern citation indicators that go beyond
simple counts.
```{r setup}
library(scimapR)
corpus <- sm_example_corpus(seed = 42)
```
## Classical indices
```{r h-index}
h <- sm_metric_h_index(corpus, level = "author")
head(h, 10)
```
## CD index (disruption)
The CD index (Funk & Owen-Smith, 2017) measures whether a work
consolidates or disrupts its field.
```{r disruption}
cd <- sm_metric_disruption(corpus)
head(cd)
```
## Relative Citation Ratio
The RCR (Hutchins et al., 2016) normalises citations relative to the
co-citation network.
```{r rcr}
rcr <- sm_metric_rcr(corpus)
head(rcr)
```
## Field-Normalized Citation Impact
FNCI (Waltman et al., 2011) normalises by field and year.
```{r fnci}
fnci <- sm_metric_fnci(corpus)
head(fnci)
```
## Uzzi novelty
Measures atypical journal combinations in reference lists (Uzzi et al., 2013).
```{r novelty}
nov <- sm_metric_novelty(corpus)
head(nov)
```
## Summary tables
```{r summary}
sm_summary_authors(corpus) |> head(5)
```
## Self-citation and self-corrected indices
`sm_self_citation()` derives author (or institution) self-citation from the
reference lists already in the corpus --- no per-citation API calls. It returns
per-entity and per-work tibbles plus a provenance trail showing which works
drove each self-citation, suitable for an institutional report.
```{r self-citation}
sc_corpus <- readRDS(system.file("extdata", "example_self_citation_corpus.rds",
package = "scimapR"))
sc <- sm_self_citation(sc_corpus, level = "author")
sc$by_entity
head(sc$provenance)
```
The h/g/m indices accept `self_corrected = TRUE`, which recomputes the index
after removing those self-citations (always `<=` the uncorrected value):
```{r self-corrected}
merge(
sm_metric_h_index(sc_corpus, "author"),
sm_metric_h_index(sc_corpus, "author", self_corrected = TRUE),
by = "author_id", suffixes = c("", "_corrected")
)
```
## References
- Funk, R. J. & Owen-Smith, J. (2017). A Dynamic Network Measure of
Technological Change. *Management Science*, 63(3), 791--817.
- Hutchins, B. I. et al. (2016). Relative Citation Ratio (RCR).
*PLOS Biology*, 14(9), e1002541.
- Waltman, L. et al. (2011). Towards a new crown indicator.
*Scientometrics*, 87(3), 467--481.
- Uzzi, B. et al. (2013). Atypical Combinations and Scientific Impact.
*Science*, 342(6157), 468--472.
