Historians and journalists alike have long prized one source of information above all others: the on-the-record, primary source. They scour the attics for diaries and journals and fly across the country for interviews. But now we have a glut of documentation.
Thanks to social media, millions of people go on the record, publicly, every single day. People sent billions of tweets, Facebook posts, and WhatsApp messages last year. They have expressed wonder 😮, anger 😤, and love ❤️ for social and political issues.
At present, most journalists treat social sources like they would any other — individual anecdotes and single points of contact. But to do so with a handful of tweets and Instagram posts is to ignore the potential of hundreds of millions of others.
Many stories lay dormant in the vast amounts of data produced by everyday consumers because journalists are still only starting to acquire the large-scale data-wrangling expertise needed to tap them. As more and more people conduct their lives online, and as smartphones are penetrating previously unconnected regions around the world, this trove of stories is only becoming larger.
The kinds of stories journalists can tell using this data are wide ranging. We can reconstruct online encounters in ways more precise than a source may recall from memory. Le Monde, for instance, retraced the journey of Syrian refugees through their WhatsApp messages. At Al Jazeera America, we analyzed and chronicled the evolution of a Hong Kong pro-democracy movement in Facebook chatrooms.
Journalists can try to find insight to people’s personality and character or hold powerful people accountable. Data scientist David Robinson did a sentiment analysis of Donald Trump’s tweets and found that Trump’s own tweets are much more negative than those his campaign staff tweeted. My colleague Charlie Warzel and I looked at the links Trump tweeted to explore the news he chooses to circulate, as a proxy for the news he may consume.
Journalists can examine the ways in which technology disadvantages groups by looking at social data. ProPublica’s Julia Angwin and Terry Parris Jr. bought a Facebook ad and established that the social media company allows advertisers to exclude customers based on race, while Vox’s Alvin Chang expanded on ProPublica’s analysis by looking at whether Facebook’s algorithm excludes already disadvantaged populations from being offered opportunities that their more affluent counterparts receive.
When journalists venture into this kind of story mining, I hope that they also continue to discuss the ethics surrounding it, the blurred lines between what is considered public and what is considered private, and the caveats that come with each dataset.
Last but not least, I hope that journalists will dig into social data to gain insights into whom they reach and, perhaps more importantly, whom they do not reach. People live in their filtered worlds in which algorithms serve them information that tends to affirm rather than question political views.
Maybe social data can allow us to understand these bubbles better in an effort to pierce them.
Lam Thuy Vo is a fellow in BuzzFeed’s Open Lab for Journalism, Technology, and the Arts.