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<h1>Author Roles and Author Positions</h1>
<pre><code class="r">library(ggplot2)
</code></pre>
<pre><code>## Warning: package 'ggplot2' was built under R version 2.15.2
</code></pre>
<pre><code class="r">
pac <- read.csv("data/plos_author_contributions.csv", row.names = NULL)
</code></pre>
<p>You can also embed plots, for example:</p>
<pre><code class="r">main.roles <- c("Conceived and designed the experiments", "Performed the experiments",
"Analyzed the data", "Contributed reagents/materials/analysis tools", "Wrote the paper")
normalised.main.roles <- tolower(sub("^(\\w+).+$", "\\1", main.roles))
pac$num.contribs <- with(pac, Conceived.and.designed.the.experiments + Performed.the.experiments +
Analyzed.the.data + Contributed.reagents.materials.analysis.tools + Wrote.the.paper)
counts.conceived <- aggregate(Conceived.and.designed.the.experiments ~ Author.Position,
pac, sum)
counts.conceived$role <- "conceived"
names(counts.conceived) <- c("position", "count", "role")
counts.performed <- aggregate(Performed.the.experiments ~ Author.Position, pac,
sum)
counts.performed$role <- "performed"
names(counts.performed) <- c("position", "count", "role")
counts.analyzed <- aggregate(Analyzed.the.data ~ Author.Position, pac, sum)
counts.analyzed$role <- "analyzed"
names(counts.analyzed) <- c("position", "count", "role")
counts.contributed <- aggregate(Contributed.reagents.materials.analysis.tools ~
Author.Position, pac, sum)
counts.contributed$role <- "contributed"
names(counts.contributed) <- c("position", "count", "role")
counts.wrote <- aggregate(Wrote.the.paper ~ Author.Position, pac, sum)
counts.wrote$role <- "wrote"
names(counts.wrote) <- c("position", "count", "role")
counts <- rbind(counts.conceived, counts.performed, counts.analyzed, counts.contributed,
counts.wrote)
for (role in normalised.main.roles) {
m <- counts$role == role
counts$rel.count[m] = counts$count[m]/sum(counts$count)
}
</code></pre>
<pre><code class="r">ggplot(subset(counts, position <= 20), aes(x = position, y = role)) + geom_point(aes(size = rel.count))
</code></pre>
<p><img 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" alt="plot of chunk unnamed-chunk-3"/> </p>
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