<p><div><div><div><div data-show-faces="false" data-height="21" data-width="100" data-layout="button_count" data-send="true" data-href="https://www.r-bloggers.com/mapping-ecosystems-of-software-development/"></div></div><div></div></div><div></div></div>
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(This article was first published on <strong><a href="https://juliasilge.com/blog/tag-network/"> Rstats on Julia Silge</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<p>I have a <a rel="nofollow" href="https://stackoverflow.blog/2017/10/03/mapping-ecosystems-software-development/" target="_blank">new post on the Stack Overflow blog</a> today about the complex, interrelated ecosystems of software development. On the data team at Stack Overflow, we spend a lot of time and energy thinking about tech ecosystems and how technologies are related to each other. One way to get at this idea of relationships between technologies is <strong>tag correlations</strong>, how often technology tags at Stack Overflow appear together relative to how often they appear separately. One place we see developers using tags at Stack Overflow is on their <a rel="nofollow" href="https://stackoverflow.com/users/story/join" target="_blank">Developer Stories</a>. If we are interested in how technologies are connected and how they are used together, developers’ own descriptions of their work and careers is a great place to get that.</p>
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<img src="https://i0.wp.com/juliasilge.com/figs/2017-10-03-tag-network/interactive_viz.gif?w=456&ssl=1" data-recalc-dims="1">
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<p>I released the data for this network structure as a <a rel="nofollow" href="https://www.kaggle.com/stackoverflow/stack-overflow-tag-network/" target="_blank">dataset on Kaggle</a> so you can explore it for yourself! For example, the post for Stack Overflow includes an interactive visualization created using the <a rel="nofollow" href="https://christophergandrud.github.io/networkD3/" target="_blank">networkD3</a> package but we can create other kinds of visualizations using the <a rel="nofollow" href="https://github.com/thomasp85/ggraph" target="_blank">ggraph</a> package. Either way, trusty <a rel="nofollow" href="http://igraph.org/r/" target="_blank">igraph</a> comes into play.</p>
<pre><code>library(readr)
library(igraph)
library(ggraph)

stack_network &lt;- graph_from_data_frame(read_csv(&quot;stack_network_links.csv&quot;),
                                       vertices = read_csv(&quot;stack_network_nodes.csv&quot;))

set.seed(2017)
ggraph(stack_network, layout = &quot;fr&quot;) +
    geom_edge_link(alpha = 0.2, aes(width = value)) +
    geom_node_point(aes(color = as.factor(group), size = 10 * nodesize)) +
    geom_node_text(aes(label = name), family = &quot;RobotoCondensed-Regular&quot;,
                   repel = TRUE) +
    theme_graph(base_family = &quot;RobotoCondensed-Regular&quot;) +
    theme(plot.title = element_text(family=&quot;Roboto-Bold&quot;),
          legend.position=&quot;none&quot;) +
    labs(title = &quot;Stack Overflow Tag Network&quot;,
         subtitle = &quot;Tags correlated on Developer Stories&quot;)</code></pre>
<p><img src="https://i0.wp.com/juliasilge.com/blog/2017/2017-10-03-tag-network_files/figure-html/unnamed-chunk-1-1.png?w=450&ssl=1" data-recalc-dims="1"></p>
<p>We have explored these kinds of network structures using all kinds of data sources at Stack Overflow, from Q&amp;A to traffic, and although we see similar relationships across all of them, we really like Developer Stories as a data source for this particular question. Let me know if you have any comments or questions!</p>
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<div>To <strong>leave a comment</strong> for the author, please follow the link and comment on their blog: <strong><a href="https://juliasilge.com/blog/tag-network/"> Rstats on Julia Silge</a></strong>.</div>
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