Safeguard Your Platform with AI Fake Profile Detection

Written by
Harriet O'Connor
Mar 22, 2024
Fake profile detection using machine learning | How to detect fake profiles | AI Fake Profile Detection

The internet is increasingly populated by a silent yet deadly threat: fake accounts.

A staggering 19% of X (Twitter) accounts are fake, 10% of online dating profiles don't represent real people, and Facebook has wiped out 27 billion fake accounts since October 2017 - that's 3.5 times the world's population!

What’s even more astonishing is that one in three US social media users juggle multiple accounts on their go-to platforms. While some may be for inoffensive purposes, allowing bad actors in disguise to roam free on your platform can be detrimental. Not only do they put user safety at risk, but they can severely damage your platform’s reputation and even jeopardize its future.

As the sophistication of these imposters’ methods continues to grow, it has never been more critical for platforms to employ AI fake profile detection methods. Read on to find out how Pasabi offers cutting-edge solutions designed to preserve the safety and authenticity of online spaces.

It’s become too easy to create fake accounts

Fabricating realistic-sounding accounts has become surprisingly easy, thanks to recent leaps in the advancement of AI. Technology such as deepfakes and ChatGPT are helping fraudsters pass off as genuine platform users due to linguistic fluency, believable images, and behavioral simulation.

Read our recent article to learn the cunning ways bad actors are leveraging AI technology to create credible-sounding online identities and bypass traditional ID verification systems.  

What happens when bad actors get onto your platform?

When bad actors infiltrate your platform through fake accounts, the consequences can be extremely damaging to your platform and users:

  • Scams: Fake profiles often lure innocent users into phishing attacks, romance scams and other fraudulent schemes, leading to financial loss, personal information theft and emotional distress.
  • Fake reviews: By posting untruthful endorsements or criticisms, these profiles can manipulate perceptions, misleading customers and hindering genuine businesses.
  • Counterfeit selling: Platforms become breeding grounds for counterfeit goods sold by fake accounts, undermining legitimate businesses, deceiving consumers and putting them at risk.
  • Spam: Unsolicited content and messages can flood users' inboxes, negatively affecting the user experience and cluttering the platform with irrelevant information.
  • Spread of misinformation: Disseminating false or misleading information to sway public opinion, disrupt events, or influence political processes.
  • Cyberbullying: Harassing or bullying individuals, often anonymously, leading to emotional distress and harm.
Fake profile detection using machine learning | How to detect fake profiles | AI Fake Profile Detection

However, the impact of these threats extends beyond the immediate harm to individual users, targeting the foundation of your platform's reputation and its long-term success.

Fake profiles erode user trust, which is the cornerstone of any online community or marketplace. The activities they enable can attract negative media attention, scrutiny from regulatory bodies, and be spread by word of mouth, damaging the platform's public image and credibility. When users feel unsafe or suspect that interactions and transactions may not be genuine, their engagement and loyalty dwindle, leading to a decline in active participation and, consequently, revenue.

How to detect fake profiles on your platform

Due to their sophistication, finding these fraudsters can feel like searching for a needle in a haystack. However, identifying the following tell-tale signs is the first step towards tackling the issue.

  • Unusual activity patterns: Rapid increases in account creations or messages that do not correlate with normal user behavior.
  • Profile Inconsistencies: Profiles with limited or no personal information, generic profile photos, or photos that can be easily found elsewhere online.
  • Erratic engagement: Accounts that have an abnormal ratio of followers to following, or that exhibit unusually high levels of engagement in a short period.
  • Spammy content: Posts or messages that are repetitive, irrelevant, or contain phishing links and suspicious content.
  • Anomaly in reviews: A sudden surge in overly positive or negative reviews that seem disconnected from the user experience.
  • Behavioral red flags: Accounts that only engage in promotional activities, without any genuine interaction with the community.
  • Network patterns: Groups of accounts that seem interconnected through their interactions, possibly indicating coordinated fake activities.

While these steps can help identify whether your platform is grappling with fake accounts, managing this issue internally can be a difficult and resource-intensive task. With the scale of the issue increasing so rapidly, fake profile detection using machine learning has become the most effective solution.

Fake profile detection using machine learning

Machine learning is a subset of artificial intelligence involving algorithms that learn from data to make decisions or predictions. As the sophistication and scale of fake accounts increases at an alarming rate, manually sifting through profiles becomes an impossible task. By automating the detection process, machine learning analyzes patterns and behaviors at scale that would be impossible for humans to match, freeing up valuable time and resources to be redirected elsewhere.

Fake profile detection using machine learning | How to detect fake profiles | AI Fake Profile Detection

At Pasabi, we use AI and machine learning to offer a targeted solution for fake profile detection with unparalleled accuracy. Our software specializes in continuous monitoring of user behavior to look for risk signals, allowing for the proactive identification of potential threats. By identifying complex networks of fake accounts and isolating significant risk patterns, Pasabi’s technology equips your platform with the information needed to take action against bad actors.

With Pasabi’s fake profile detection, you can take action at a granular level. Our solution gives you the evidence you need to block or delete profiles associated with fraudulent account activity. Additionally, we provide continual monitoring of your platform to ensure their ongoing detection, protecting your users and reputation effectively.

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