Reading Metadata to Combat Disinformation and Fake News CampaignsSandlin, Anu  | Jan 22, 2019
If you’ve ever reacted to a Facebook post, retweeted on Twitter, or commented on an Instagram story, then you’ve not only successfully used and engaged with these communication infrastructures, but you’ve also created your own digital trace of “metadata,” which Texas School of Information Assistant Professor Amelia Acker defines as “an index of human behavior.”
Our activity on social platforms –such as favorites, likes, retweets, comments, and reactions are used mostly to advertise to us, but there is a dark side where manipulators, bots, and people in the business of disinformation and misinformation try to “appear human to the algorithms that police social networks,” says Acker, who is also a Research Affiliate at Data & Society Research Institute’s Media Manipulation Initiative.
Acker dubs the manipulation of this information “data craft –a collection of practices that create, rely on, or even play with the proliferation of data on social media by engaging with new computational and algorithmic mechanisms of organization and classification.”
In summer 2018, New Knowledge, a local data science firm in Austin, Texas, published findings about Russian-connected Twitter bots and fake Facebook accounts which were used to manipulate public discourse during the 2016 U.S. election. “Some of these hoaxes and fakes are rather crafty in their ability to circumvent the boundaries of platforms and their terms of service agreements” notes Acker. From election tampering to shifting political discourse around social debates like immigration reform and racial politics, Acker explains that the presence of false activity data has had a number of unpredictable consequences for social media users and society.
Data craft is becoming more harmful because “more than half of Americans get their news primarily from social media,” says Acker. And this problem isn’t going away anytime soon. In fact, it’s about to get a lot worse as “bots are starting to mimic our social media activity to look more human” and ‘sockpuppets’ are becoming “more and more sophisticated to where they can now craft data to look like real user engagement with conversation online,” explains Acker.
By identifying and understanding disinformation tactics as data craftwork, information researchers can read social media metadata just as closely as algorithms do, and possibly with more precision than the platforms’ moderation tools.
With those in the business of data craft becoming smarter and craftier at faking what looks like authentic behavior on social media, what does this mean for us? Put simply, it will become more difficult for us to discern ‘real’ users and authentic account activities from fake, spammy, and malicious manipulations,” said Acker in a recent Data & Society report.
But there is a sense of hope, which according to Acker, lies in the metadata itself. “Metadata features such as account name, account image, number of likes, tags, and date of post can provide activity frequency signals that serve as clues for suspicious activity.” “Reading metadata surrounding sockpuppet accounts will often reveal intentions, slippages, and noise –which can further reveal automated manipulation,” claims Acker.
“By identifying and understanding disinformation tactics as data craftwork, information researchers can read social media metadata just as closely as algorithms do, and possibly with more precision than the platforms’ moderation tools,” says Acker.Closely examining metadata such as the rapidity of account activity, follower/audience counts, post timestamps, media content, user bios, and location data, has led to thousands of fake accounts being detected by social media researchers and tech journalists.
So while we may not be able to beat bots and manipulators at their data craft game, the future is hopeful when it comes to detecting and identifying disinformation. Understanding data craft and how it can manifest in the world of social media and metadata is the first step. The second is reading metadata that has been gamed, exploited, or changed. This, according to Acker, promises a new method for tracing the spread of misinformation and disinformation campaigns on social media platforms. It will also improve data literacy among citizens by providing a method to judge whether messages are authentic or deceptive.
Acker plans to use the case studies of “reading metadata” in her INF384M Theories and Applications of Metadata course in spring 2019 at the Texas iSchool. She hopes that her research will help educators, journalists, policy makers, technologists, and early-career professionals like students understand how bad actors can manipulate metadata to create disinformation campaigns. “The acquisition of this information and understanding is empowering and gives us an advantage in terms of deciphering which information is real and which is fake or manipulated.”
For additional tips on reading metadata, see Dr. Amelia Acker’s latest Data & Society report: The Manipulation of Social Media Metadata.