How Viral Spikes Shape Digital Movements

Visualization

Each user is a gray dot. Scroll around to see all of the users. Drag through the timeline to explore different months of user activity. A user will light up with colored circles and turn black if they have tweeted that month, color coded to coorespond with the colors listed below. A light gray user indicates that the user hasn't tweeted within the month.

Some key months to examine are November 2014 (Black Lives Matter), July 2016 (Blue Lives Matter), September-October 2017 (Me Too), and May-June 2020 (Black Lives Matter). Climate generally appears throughout the timeline but one subtle spike of activity is in November 2021. Note how quickly people move on to the next issue, and stop paying attention to the previous issue.

Analysis

Before social media, movements met up in person, disrupted events with protests, and made noise in real life. Today, most of that happens online. There are still protests and there are still real live meetings and discussions but those are just the tips of the iceberg. Today, the majority of the conversations and collaboration toward change occur online.

We created our visualization to explore how different social movements captured the attention of social media users, or in other words, to examine their visibility and reach. This is because traditional media used to operate as a monopoly on public attention - it could decide not to cover a movement for ideological or corporate reasons. Thus movements used to rely on mass media to publicize their cause and events to tell their story. Since today’s movements are largely online, there is less of a reliance on mass media to tell this story. Instead, movements rely on social media to tell their story which means that it is important for modern-day social movements to understand how and why movements go viral so that they can take advantage of 'the algorithm' to get their message out.

We wanted to help future movement leaders figure out how to navigate what happens below the surface. What they, in large part, don’t get to see. Sure they see some tweets but that is only the slice that algorithms want to show them. The above visualizaiton displays a random sample of around 12k twitter users randomly picked from the total list of tweets about about Black Lives Matter and the Me Too movement. Movement leaders can watch as movements thrive and wilt and how individual users become engaged and subsequently become disengaged with the movement. The cyclical pulsing of these movements makes it obvious that these movements are driven by attention-driven algorithms. This emphasizes the need for movements to both be prepared for spikes in engagement and for the hijacking of movements (such as how Blue Lives Matter hijacked Black Lives Matter in 2016).

As shown above, digital movements appear to experience spikes of activity followed by periods of relative quiet. Movements should prepare for these viral spikes and also be sure to encourage off-platform engagement with the movement during those spikes so that passionate supporters can continue to support the movement even when the algorithm moves onto the next viral topic.