Thread by @conspirator0

Here's a network graph for a popular hashtag. Since the graph has no labels, you can't tell what hashtag it is, or what anything in the graph actually means, but it's colorful and pretty and weird and therefore incredibly tempting to retweet, right?

cc: @ZellaQuixote

The hashtag in question is #CatsOfTwitter, and here's a more boring-looking version of the same graph with more context. The interaction being graphed is retweets, with the more frequently-retweeted accounts shown larger on the graph, and the date range is also included.

One can alter the apparent meaning of a graph via manual editing. Here, three of the accounts have been dragged off to the top left, suggesting a relationship between them that isn't supported by the underlying data. It's technically still "correct", but it's misleading.

Graphs can also be misleading if one highlights a particular aspect without exploring it. Here, the retweets from bots (automated accounts) have been colored pink, revealing what appears to be a cluster of automated activity. Is this some kind of nefarious #CatsOfTwitter botnet?

Nope. Changing settings so that the label size is proportional to the number of times the account retweeted a #CatsOfTwitter tweet (rather than the number of times the account was retweeted) reveals that almost all of the automated activity is from just two accounts.

Overall point: while data visualizations are very useful and effective (and sometimes pretty) ways of summarizing lots of data, context is vital to interpreting them and should always be included.

Footnote: for this portion of the thread, automation was determined based on the source app used to post the tweet/retweet as provided by the Twitter API.