Twitter doesn’t make it easy to examine the history of a trending topic or its origins. But based on our analysis of 1,000 tweets using the hashtag, scraped in real-time for a portion of its time on the trending list last night, it’s pretty unlikely that the main momentum driving the hashtag up the trending list came from the relatively small group of Trump supporters and alt-right trolls who tweeted about it.
Instead, it seems that, at the very least, the momentum keeping #Repealthe19th in the trending list came from people who were furious that the hashtag existed at all.
We’ll acknowledge that judging this sort of thing is subjective at best, but looking through 1,000 tweets and retweets scraped between 7:50 and 9:10 p.m. Wednesday, a little more than 100 of them appear to be from Trump supporters. The rest are all expressing outrage about the hashtag, rallying women to get out and vote in response to it, or are straight-up mocking it.
How did we get here? Let’s start with the hashtag itself.
#Repealthe19th is a real, anti-feminist hashtag that sits at the intersection of the alt-right’s sense of humor and genuine misogyny. It’s been around for a long time, popping up in tweets mocking women to provoke a response, or (more recently) as a way to meme and joke about Trump’s lagging support with women voters.
The sort of people who think it’s funny to try to “trigger” feminists online by tweeting offensive things at them would read #Repealthe19th as a joke hashtag, something that’s borne out by its popularity during the past few months. According to Indiana University’s trend analysis tools, the last time the hashtag spiked was around Aug. 18, or the anniversary of the day the 19th Amendment was ratified, har har.
This time, #Repealthe19th caught the attention of reporters Wednesday, a day after Nate Silver tweeted a pair of electoral maps. One showed the electoral map if only men voted, and the other showed the same with only women voting. The latter was much more favorable to Hillary Clinton:
The map of only male voters showed Trump handily winning the presidency.
Those tweets triggered a round of #RepealThe19th responses from alt-righters on Tuesday and Wednesday, including one from a now-suspended account with the handle @smugpepe1488. Here are a couple others:
The Indiana University’s trend analysis tools have a lag time, so we’re limited in our ability to see exactly when #Repealthe19th started to spike this time.
Our best guess is that the spike came after the Los Angeles Times published a widely cited short article Wednesday afternoon about the “new” hashtag, which it observed popping up in response to Nate Silver’s analysis, and quoted several tweets using it. That article went up at about 3:30 Eastern time; the first tweets we can find noting that the hashtag was “trending” on Twitter came less than an hour after that.
Based on our analysis, it seems unlikely that the momentum driving all that growth came from people who supported the idea contained in the hashtag.
Sure, there are definitely some popular tweets from Wednesday that do seem to do exactly that:
But overwhelmingly, the most influential tweets we could identify about #Repealthe19th over the course of yesterday appear to come from people who are very much opposed to the hashtag, according to a network analysis of the hashtag we generated using Indiana University’s social analysis tool suite.
Tweets like Takei’s, and these:
All three of which repeatedly showed up as retweets in the small sample of tweets we scraped yesterday evening.
As it turns out, we’ve seen this all before. The hashtag #StopIslam trended in March, just after the attacks in Belgium. But as our analysis then demonstrated, the trending topic was largely driven by people criticizing it. And that phenomenon itself fell in line with the findings of researchers who analyzed anti-Muslim sentiment on social media after the Paris attacks.
Anti-Muslim rhetoric spikes disturbingly on social media after an attack, but the spike of anti-anti-Muslim rhetoric is even more dramatic.In that study, a team of three computer scientists found that racist and bigoted messages are spread primarily by small numbers of people with small followings, sharing the same hashtag multiple times. Anti-bigotry messages, on the other hand, are spread by larger and more diffuse numbers of people who are more central to the information network online.
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Correction: An earlier version of this article incorrectly referred to Indiana University as the University of Indiana.