rAltmetric
This package provides a way to programmatically retrieve altmetrics from various publication types (books, newsletters, articles, peer-reviewed papers and more) from altmetric.com. The package is really simple to use and only has two major functions:
altmetrics- Pass it a doi, isbn, uri, arxiv id or other to get metricsaltmetric_dataPass it the results from the previous call to get a tidydata.frame
Questions, features requests and issues should go here.
Installing the package 🛠
A stable version is available from CRAN. To install
install.packages('rAltmetric')
# or the 👷 dev version
devtools::install_github("ropensci/rAltmetric")Quick Tutorial
Obtaining metrics
There was a 2010 paper by Acuna et al that received a lot of attention on Twitter. What was the impact of that paper?
library(rAltmetric)
acuna <- altmetrics(doi = "10.1038/465860a")
acuna
#> Altmetrics on: "Metrics: Do metrics matter?" with altmetric_id: 385053 published in Nature.
#> stats
#> cited_by_fbwalls_count 3
#> cited_by_feeds_count 3
#> cited_by_gplus_count 2
#> cited_by_msm_count 1
#> cited_by_policies_count 1
#> cited_by_posts_count 31
#> cited_by_tweeters_count 20
#> cited_by_accounts_count 30Data
To obtain the metrics in tabular form for further processing, run any object of class altmetric through altmetric_data() to get a data.frame that can easily be written to disk.
altmetric_data(acuna)
#> title doi pmid
#> 1 Metrics: Do metrics matter? 10.1038/465860a 20559361
#> tq1
#> 1 Survey of how metrics are used in hiring, promotion and tenure decisions.
#> tq2
#> 1 Should some professions be excluded from performance metrics? #metrics #kpi #performancemeasurement
#> tq3
#> 1 “@Nanomedicina: Publications: Do metrics matter?
#> tq4 altmetric_jid
#> 1 Do metrics matter? #oaweek13 (in talk @pgroth ) 4f6fa50a3cf058f610003160
#> issns1 issns2 journal cohorts.pub cohorts.sci cohorts.com
#> 1 0028-0836 1476-4687 Nature 13 5 2
#> context.all.count context.all.mean context.all.rank context.all.pct
#> 1 7133716 6.3030007714043 130911 98
#> context.all.higher_than context.journal.count context.journal.mean
#> 1 7003174 44393 68.76030910975
#> context.journal.rank context.journal.pct context.journal.higher_than
#> 1 10546 76 33847
#> context.similar_age_3m.count context.similar_age_3m.mean
#> 1 76598 5.330816089403
#> context.similar_age_3m.rank context.similar_age_3m.pct
#> 1 1082 98
#> context.similar_age_3m.higher_than context.similar_age_journal_3m.count
#> 1 75516 894
#> context.similar_age_journal_3m.mean context.similar_age_journal_3m.rank
#> 1 54.580732362822 262
#> context.similar_age_journal_3m.pct
#> 1 70
#> context.similar_age_journal_3m.higher_than type altmetric_id schema
#> 1 632 news 385053 1.5.4
#> is_oa cited_by_fbwalls_count cited_by_feeds_count cited_by_gplus_count
#> 1 FALSE 3 3 2
#> cited_by_msm_count cited_by_policies_count cited_by_posts_count
#> 1 1 1 31
#> cited_by_tweeters_count cited_by_accounts_count last_updated score
#> 1 20 30 1454625692 53.388
#> history.1y history.6m history.3m history.1m history.1w history.6d
#> 1 0 0 0 0 0 0
#> history.5d history.4d history.3d history.2d history.1d history.at
#> 1 0 0 0 0 0 53.388
#> url added_on published_on subjects
#> 1 http://dx.doi.org/10.1038/465860a 1317207766 1276646400 science
#> scopus_subjects readers.citeulike readers.mendeley readers.connotea
#> 1 General 3 303 2
#> readers_count
#> 1 308
#> images.small
#> 1 https://altmetric-badges.a.ssl.fastly.net/?size=64&score=54&types=mbtttfdg
#> images.medium
#> 1 https://altmetric-badges.a.ssl.fastly.net/?size=100&score=54&types=mbtttfdg
#> images.large
#> 1 https://altmetric-badges.a.ssl.fastly.net/?size=180&score=54&types=mbtttfdg
#> details_url
#> 1 http://www.altmetric.com/details.php?citation_id=385053You can save these data into a clean spreadsheet format:
acuna_data <- altmetric_data(acuna)
readr::write_csv(acuna_data, path = 'acuna_altmetrics.csv')Gathering metrics for many DOIs
For a real world use-case, one might want to get metrics on multiple publications. If so, just read them from a spreadsheet and llply through them like the example below.
library(rAltmetric)
library(magrittr)
#>
#> Attaching package: 'magrittr'
#> The following object is masked from 'package:purrr':
#>
#> set_names
#> The following object is masked from 'package:tidyr':
#>
#> extract
library(purrr)
ids <- list(c(
"10.1038/nature09210",
"10.1126/science.1187820",
"10.1016/j.tree.2011.01.009",
"10.1086/664183"
))
alm <- function(x) altmetrics(doi = x) %>% altmetric_data()
results <- pmap_df(ids, alm)
# This results in a data.frame with one row per identifier.Further reading
rAltmetric in publications use:
Karthik Ram (2017). rAltmetric: Retrieves altmerics data for any
published paper from altmetrics.com. R package version 0.7.
http://CRAN.R-project.org/package=rAltmetric
A BibTeX entry for LaTeX users is
@Manual{,
title = {rAltmetric: Retrieves altmerics data for any published paper from
altmetrics.com},
author = {Karthik Ram},
year = {2017},
note = {R package version 0.7},
url = {http://CRAN.R-project.org/package=rAltmetric},
}