Computes the Relative Citation Ratio (RCR) for each work in the corpus. RCR normalises citation counts by the expected citation rate of works in the same field and publication year, providing a field-normalised measure of scientific influence.
Usage
sm_metric_rcr(corpus, baseline = "field_year", call = rlang::caller_env())Arguments
- corpus
An sm_corpus object.
- baseline
Character; the normalisation baseline. Currently only
"field_year"is supported, which normalises by field (derived from concepts) and publication year.- call
Caller environment for error reporting.
Value
A tibble with columns work_id, cited_by_count, expected_rate,
and rcr. Works without sufficient data receive NA for rcr.
Details
The RCR is calculated as:
$$RCR = \frac{C_i}{E_i}$$
Where:
- C_i
The citation count of work i.
- E_i
The expected citation count, computed as the mean citation count of works in the same field-year group.
Field assignment uses the top-level concept (level 0) from the concepts table. Works without concept assignments are grouped into an "unclassified" field.
An RCR of 1.0 means the work is cited at the average rate for its field-year. Values above 1.0 indicate above-average impact.
References
Hutchins, B. I., Yuan, X., Anderson, J. M., & Santangelo, G. M. (2016). Relative Citation Ratio (RCR): A New Metric That Uses Citation Rates to Measure Influence at the Article Level. PLOS Biology, 14(9), e1002541. doi:10.1371/journal.pbio.1002541
Examples
corpus <- sm_example_corpus()
rcr <- sm_metric_rcr(corpus)
head(rcr)
#> # A tibble: 6 × 4
#> work_id cited_by_count expected_rate rcr
#> <chr> <int> <dbl> <dbl>
#> 1 W000000001 3 10.2 0.293
#> 2 W000000002 9 12.2 0.738
#> 3 W000000003 28 11.3 2.47
#> 4 W000000004 29 27.5 1.05
#> 5 W000000005 16 16 1
#> 6 W000000006 16 16 1