Fake Twitter followers are useless. Don’t buy them. That’s the conventional advice given by any social media authority to anyone interested in building up their social media footprint. Don’t buy fake Twitter followers. Don’t buy any fake followers. Instead, experts will advise earning followers the “old-fashioned” way; through honest, authentic engagement. Why? Because real community-building increases loyalty, brand advocacy, and trust. In this way, your community becomes your customers. An article from the marketing experts at Moz succinctly summed up this truism when they wrote that “adding legit Twitter followers will increase engagement and impressions because actual people will be retweeting you, replying to your posts, or otherwise interacting with your content.” Why Do Fake Twitter Followers Even Exist? If it’s true that fake followers don’t work as a marketing strategy, why are there still so many fake followers? Well, for one thing, not everyone subscribes to the above advice. We still live in a world in which follower counts are considered evidence of value and success, and as long as that remains the case, people will continue to try and inflate their social media presence with fake followers. There is another, far more malicious reason why fake followers still exist. Fraudsters make money with them. Not just by selling them, but by using them to deceive you, and steal from you. To make one thing very clear, fake Twitter followers are bots. They’re not real people. Fraudsters create them, and then use them for all sorts of illicit purposes, including fake news dissemination, online abuse, fake reviews, content abuse, ad fraud, and spam. Often, the accounts are created in the wake of identity theft. Fake Followers are Bots, and They’re Stealing Your Identity A 2018 article from the New York Times exposed the practices of a company called Devumi that sells fake followers; often, as the article makes clear, these accounts are created using personal information stolen from legitimate user accounts: “The accounts that most resemble real people … reveal a kind of large-scale social identity theft. At least 55,000 of the accounts use the names, profile pictures, hometowns and other personal details of real Twitter users, including minors.” Instagram, one of the largest social media platforms in the world, has waged a long and public battle against fake accounts, and while much of the media coverage focuses on trying to “out” influencers for not being as popular as they claim, there are much bigger issues at stake, as a recent article from The Independent made clear. The post quotes Pete Hunt, CEO of Smyte, who says, “Bots are also used to attack people. The bot may be befriending you so it can send you private messages with spam or phishing attempts.” The article goes on to cite a study by Imperva, noting that “these bad bots, the ones that want to steal your password or infect you with a virus, account for 28.9% of bots on Instagram.” Finally, the article makes clear that “If your Instagram is public, meaning anyone can view your pictures, the risk of bots following you, messaging you, and stealing your photos is increased.” In short, fake followers are, in fact, predatory bots, built to defraud, deceive, and destabilize otherwise legitimate platforms. The Move to Purge Fake Followers We know fake followers are bad marketing. We’ve known this for a while. It was all the way back in 2012 that Lady Gaga’s then-record-breaking follower account was exposed for being 71% fake. These days, companies are finally taking steps to address the issue: Instagram Is Purging Fake Followers From the App In Twitter Purge, Top Accounts Lose Millions of Followers Facebook Cracks Down on Companies Selling Fake Likes, Followers, and Accounts For Twitter, this was a bold move, but also a risky one: Twitter stock plunges 21% after earnings show effects of fake-account purge It paid off. As of August 30, 2019, Investor’s Business Daily listed Twitter as being among the fastest-growing stocks of 2019. The Many Victims of Fake Account and Fake Follower Fraud When fake accounts are used for phishing, spam, and other types of fraud attacks, there are many victims. Individuals on the receiving end of phishing attacks on social media can be duped into sharing personal information that can, in turn, lead to their accounts being compromised. Businesses that maintain active social profiles can unwittingly engage with bots and inadvertently open up vulnerabilities that lead to data breaches by clicking on malicious links or responding to deceptive queries. Platforms that depend on reputational equity for the success of their business models suffer reputational damage when it becomes clear their platforms are infected by fake accounts. You might, at this point, be wondering if there is any good news. There is. It has to do with scale. Fraud at Scale, Detection at Scale The fake follower game is all about scale. One fake account has little chance of producing profit or other beneficial results for a fraudster. However, when a fraudster sends a million malicious bots into the world, their odds of success are considerably increased. Yet while this reliance on massive-scale operations is the key to their success, it’s also the fraudster’s Achilles heel, because operating at scale requires coordination, and coordination produces patterns that can be exposed through holistic data analysis and the use of advanced unsupervised machine learning. It’s virtually impossible to proactively detect the isolated creation of a single fake account. However, the simultaneous mass registration of thousands of fake accounts is another matter. Viewed in isolation, those accounts may still seem legitimate, but when viewed holistically, patterns, correlations, and connections are revealed that indicated coordinated fraudulent activity. Solution: Proactive, AI-Powered Fraud Prevention There is no place for fake accounts and fake followers in our digital economy. They don’t do anyone any good. However, if titans like Facebook, Instagram, and Twitter are still struggling to find and purge them, what chance do we stand of ridding the world of these chaos-causing bots, and winning the battle for truth and safety online? The answer comes down to proactivity. When you can prevent fake accounts from being created in the first place, before damage occurs, then you win. Rules-based systems won’t suffice. They’re too slow, they rely too heavily on existing labels, and they have to be re-tuned too often. They simply can’t keep up, and as DataVisor CEO and Co-Founder Yinglian Xie regularly points out: “If you are only keeping up, you are already behind.” Unsupervised machine learning, on the other hand, can expose the planning stages of a future attack. This enables organizations to block bots before they become fake followers. In this way, we make the digital world a safer place for all. View posts by tags: Account Takeover fake accounts fake twitter followers identity theft Related Content: Quick Takes Exposing the Digital Footprints of Fraud Quick Takes React, or Prevent? Why Organizations Must Embrace A Proactive Approach To Fraud Management Product Blogs Defeating Mass Registration with Unsupervised Machine Learning about Priya Rajan Priya Rajan is CMO at DataVisor. She is a highly-regarded leader in the technology and payments sectors, bringing more than two decades of experience to her role. She has previously held leadership roles with high-growth technology organizations such as VISA and Cisco, and Silicon Valley unicorns like Nutanix and Adaptive Insights. about Priya Rajan Priya Rajan is CMO at DataVisor. She is a highly-regarded leader in the technology and payments sectors, bringing more than two decades of experience to her role. She has previously held leadership roles with high-growth technology organizations such as VISA and Cisco, and Silicon Valley unicorns like Nutanix and Adaptive Insights. View posts by tags: Account Takeover fake accounts fake twitter followers identity theft Related Content: Quick Takes Exposing the Digital Footprints of Fraud Quick Takes React, or Prevent? Why Organizations Must Embrace A Proactive Approach To Fraud Management Product Blogs Defeating Mass Registration with Unsupervised Machine Learning