alm_events | R Documentation |
Events are the details of the metrics that are counted related to PLoS papers.
alm_events(doi = NULL, pmid = NULL, pmcid = NULL, wos = NULL, scp = NULL, url = NULL, source_id = NULL, publisher_id = NULL, compact = TRUE, key = NULL, api_url = "http://alm.plos.org/api/v5/articles", ...)
doi |
Digital object identifier for an article in PLoS Journals (character) |
pmid |
PubMed object identifier (numeric) |
pmcid |
PubMed Central object identifier (numeric) |
wos |
Web of Science identifier (character) |
scp |
Scopus identifier (character) |
url |
Canonical URL (character) |
source_id |
(character) Name of source to get ALM information for. One source only. You can get multiple sources via a for loop or lapply-type call. |
publisher_id |
(character) Metrics for articles by a given publisher, using the Crossref
|
compact |
(logical) Whether to make output compact or not. If TRUE (default), remove empty sources. |
key |
(character) Your API key, either enter, or loads from .Rprofile. Only required for PKP source, not the others. |
api_url |
API endpoint, defaults to http://alm.plos.org/api/v3/articles (character) |
... |
optional additional curl options (debugging tools mostly) |
You can only supply one of the parmeters doi, pmid, pmcid, and mendeley.
Query for as many articles at a time as you like. Though queries are broken up in to smaller bits of 30 identifiers at a time.
If you supply both the days and months parameters, days takes precedence, and months is ignored.
You can get events from many different sources. After calling alm_events, then index the output by the data provider you want. The options are: bloglines, citeulike, connotea, crossref, nature, postgenomic, pubmed, scopus, plos, researchblogging, biod, webofscience, pmc, facebook, mendeley, twitter, wikipedia, and scienceseeker.
Beware that some data source are not parsed yet, so there may be event data but it is not provided yet as it is so messy to parse.
See more info on PLOS's relative metrics event source here http://www.plosone.org/static/almInfo#relativeMetrics
PLoS altmetrics as data.frame's.
See a tutorial/vignette for alm at http://ropensci.org/tutorials/alm_tutorial.html
## Not run: # For one article out <- alm_events(doi="10.1371/journal.pone.0029797") names(out) # names of sources # remove those with no data out <- out[!out %in% c("sorry, no events content yet","parser not written yet")] out[["pmc"]] # get the results for PubMed Central out[["twitter"]] # get the results for twitter out[["plos_comments"]] # get the results for PLOS comments, sorta messy out[c("twitter","crossref")] # get the results for two sources # Another example (out <- alm_events(doi="10.1371/journal.pone.0001543")) # remove those with no data out <- out[!out %in% c("sorry, no events content yet","parser not written yet")] names(out) out[['scopus']] out[['mendeley']] out[['figshare']] out[['pubmed']] # Two doi's dois <- c('10.1371/journal.pone.0001543','10.1371/journal.pone.0040117') out <- alm_events(doi=dois) out[[1]] out[[2]] out[[1]][["figshare"]]$events # Many pmcid's out <- alm_events(pmcid=c(212692,2082661)) names(out) out['212692'] # Many pmid's out <- alm_events(pmid = c(19300479, 19390606, 19343216)) names(out) out['19390606'] # Specify two specific sources ## You have to do so through lapply, or similar approach lapply(c("crossref","twitter"), function(x) alm_events(doi="10.1371/journal.pone.0035869", source_id=x)) # Figshare data alm_events(doi="10.1371/journal.pone.0069841", source_id='figshare') # Datacite data alm_events("10.1371/journal.pone.0012090", source_id='datacite') # Reddit data alm_events("10.1371/journal.pone.0015552", source_id='reddit') # Wordpress data alm_events("10.1371/journal.pcbi.1000361", source_id='wordpress') # Articlecoverage data alm_events(doi="10.1371/journal.pmed.0020124", source_id='articlecoverage') # Articlecoveragecurated data headfoo <- function(x) head(x$articlecoveragecurated$events) headfoo(alm_events(doi="10.1371/journal.pone.0088278", source_id='articlecoveragecurated')) headfoo(alm_events(doi="10.1371/journal.pmed.1001587", source_id='articlecoveragecurated')) # F1000 Prime data alm_events(doi="10.1371/journal.pbio.1001041", source_id='f1000') dois <- c('10.1371/journal.pmed.0020124','10.1371/journal.pbio.1001041', '10.1371/journal.pbio.0040020') res <- alm_events(doi = dois, source_id='f1000') res[[3]] # by source_id only alm_events(source_id = "crossref") alm_events(source_id = "reddit") # by publisher_id only alm_events(publisher_id = 340) # search the software lagotto sever urls <- c("https://github.com/najoshi/sickle","https://github.com/lh3/wgsim", "https://github.com/jstjohn/SeqPrep") dat <- alm_events(url = urls, api_url = "http://software.lagotto.io/api/v5/articles") ## End(Not run)
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