Thread: just a snapshot of the increasing polarisation of the US Twittersphere ahead of the midterms.
Polarised communities proved to be an easy target for influence operations in 2014-18.
medium.com/dfrlab/electio…
Polarised communities proved to be an easy target for influence operations in 2014-18.
medium.com/dfrlab/electio…
Scanned three sets of paired election-related hashtags: #VoteRed / #VoteBlue, #RedWave2018 / #BlueWave2018, #FlipItRed / #FlipItBlue.
First scan covered 48 hours. Overall, pro-Democratic hashtags got significantly higher traffic (79k posts compared with 47k posts).
First scan covered 48 hours. Overall, pro-Democratic hashtags got significantly higher traffic (79k posts compared with 47k posts).
On this scan, users of pro-Democratic hashtags were roughly double the number of users on pro-Republican hashtags (40k users compared with 21k users).
User numbers were much closer on this scan of 100k posts on each hashtag, but what's really striking is the surge in traffic on the "red" series.
It generated the highest volume anywhere in the scan.
It generated the highest volume anywhere in the scan.
This was the post: Dinesh D'Souza on the "good guys" and the "evil party."
Clearly, in terms of online traffic, polarisation pays.
Clearly, in terms of online traffic, polarisation pays.
This doesn't just apply to one side. The top-performing post on a pro-Democratic hashtag was pretty polarising, too.
It got 11k retweets during the scan, and another 4k afterwards, just beating D'Souza in terms of retweets overall.
It got 11k retweets during the scan, and another 4k afterwards, just beating D'Souza in terms of retweets overall.
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