Disentangle Things by Ivan Hanigan

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Using scholar rankings to provide weights in systematic literature reviews part 1

I’ve been thinking alot recently about an approach used in this recent systematic review

Vins, H., Bell, J., Saha, S., & Hess, J. (2015). The mental health
outcomes of drought: A systematic review and causal process
diagram. International Journal of Environmental Research and Public
Health, 12(10), 13251–13275. doi:10.3390/ijerph121013251

They identify causal pathways from papers and ascribe the supporting evidentiary weight based on the number of papers published with findings that support this cause-effect pathway
The raw number of papers is probably not a good metric, prone to bias so I was thinking of ways to ascribe weight based on quality of journal or authors
This is not supposed to replace the need to actually read the papers, but purely as an additional source of information
This recent post on scholar metrics provided some impetus via h-indices http://datascienceplus.com/hindex-gindex-pubmed-rismed/
I also think this approach of text mining the abstracts could be useful http://tuxette.nathalievilla.org/?p=1682

Sanity check of the two options using myself as guinea pig

library(RISmed)
x <- "hanigan+ic[Author]"
res <- EUtilsSummary(x, type="esearch", db="pubmed", datetype='pdat', mindate=1900, 
  maxdate=2015, retmax=500)
str(res)
citations1 <- Cited(res)
citations <- as.data.frame(citations1)
citations <- citations[order(citations$citations,decreasing=TRUE),]
citations <- as.data.frame(citations)
str(citations)
citations <- cbind(id=rownames(citations),citations)
citations$id<- as.character(citations$id)
citations$id<- as.numeric(citations$id)
hindex <- max(which(citations$id<=citations$citations))

hindex
# 5

library(scholar)
myid <- "cGN1P0wAAAAJ"
y <- scholar::get_publications(myid)
str(y)
y[,c("author", "cites")]
y$id <- as.numeric(row.names(y))
hindex2 <- max(which(y$id<=y$cites))
hindex2
# 15