#OccupyWallStreet, the most commonly used Twitter hashtag since the start of the 99 Percent movement, has trended in Vancouver, Portland, and San Francisco…but not in New York. #OccupyBoston has trended in numerous cities across the U.S., but never in Boston itself.
In a blog post analyzing Occupy Wall Street as a trending topic, SocialFlow‘s vice president of R&D, Gilad Lotan, explores those ironies, analyzing all the OWS-related terms that have trended on Twitter since the start of the movement, their volume of appearance in tweets, and the times and locations they’ve trended.
The core of his findings: The fact that Occupy Wall Street grew over time, steadily and consistently, actually impaired its ability to trend. Trending isn’t about volume alone; Twitter’s algorithm adapts over time, Lotan notes, based on the changing velocity of the usage of the given term in tweets. In other words, it rewards spikes over steadiness. If a topic — say, #WhatYouShouldKnowAboutMe — bursts and then fades, it’ll trend. On the other hand: “If we see a systematic rise in volume, but no clear spike, it is possible that the topic will never trend, as the algorithm takes into account historical appearances of a trend.”
Twitter, though mum on the specifics of its algorithm, confirmed that explanation. “[Trending Topics] are the most ‘breaking’ and reward discussions that are new to Twitter,” the company’s communications chief explained to BetaBeat, responding to accusations that Twitter has been purposely blocking #OccupyWallStreet from trending. “We are not blocking terms related to #OccupyWallStreet in any way, shape or form.”
There are other explanations, too: Trending Topics compete with others for user attention — and #OccupyWallStreet has been up against both #ThankYouSteve and, yep, #KimKWedding. And the lack of a single hashtag for the movement overall — “splinted conversations,” Lotan calls it — likely also impeded its ability to break through.
But what’s most interesting, to me, are the assumptions baked into the Trending Topics algorithm in the first place. On the one hand, it’s perfectly fair — in fact, it’s perfectly necessary — to define “trends” as brief ruptures of the ordinary. Spikes, you know, speak. But the algorithm’s assumption is also one that’s baked into the cultural algorithm of journalistic practice: We tend, as reporters and attention-conveners, to value newness over pretty much everything else.
Again, on the one hand, that’s absolutely appropriate — “the news,” after all — but on the other, the institutional obsession with newness often impedes journalists’ ability to address the biggest issues of the day — the economy, the environment, the effects of the digital transition on global culture — within conventional narrative frameworks. Just as #OccupyWallStreet, in Twitter’s algorithm, competes against #KimKWedding, we pit the long-term and the temporary against each other, forcing them to compete for people’s (and journalists’) attention. We accept that the slow-burn stories have to fight for space against the shocking, the spiking, the evanescent.
Which is unfortunate, since the most important topics for journalists to address are often the ones that are the opposite of “trending.”