by Rey Beltran | www.executivechronicles.com
Facebook has stepped up its battle against fake likes. With the proliferation of social media, the battle for the advertisers’ ad spending has grown stiffer, to the point that “likes” are being faked, bought, and passed on as legitimate.
Marketers buy “likes” to boost their chances of selling the sites they are promoting. But that is not possible anymore. Facebook has developed some tactics to combat fraudulent likes and spamming. And for starters, they have developed pattern recognition technologies to help them curb activities coming from like farms, click farms, fake accounts, and malware.
This is what Facebook Site Integrity Engineer H. Kerem Cevahir posted in its page:
“This work has made it extremely difficult for the people selling fraudulent likes to actually deliver their promised likes to paying customers. In fact, over the the last six months, we’ve tripled the number of likes we’ve detected and blocked before they ever reached a Page. Because of this effort, a large number of the vendors that were attempting to sell inauthentic likes to Facebook Page administrators have closed their businesses.
“In addition to removing fake likes directly from Pages, we now send notifications to Page administrators when we block or remove fake likes from their Pages to help them learn how to gather authentic fans. Since introducing this feature in March 2015, we’ve notified 200,000 Pages that we’ve protected their accounts from fake likes.”
Facebook fights like spam, Jones wrote, by using machine learning tools to flag suspicious behavior. When it’s caught, accounts of violators are shut down and fake likes are removed. Facebook also limits the number of likes per account and if a user’s like activity spikes unusually, the company’s spam fighters ask for verification.
Matt Jones, another Facebook Integrity Engineer, has observed that like farms have been promising page administrators delivery of large numbers of like to their pages. Especially is these page administrators are just building up their sites.
“We have a strong incentive to aggressively go after the bad actors behind fake likes because businesses and people who use our platform want real connections and results, not fakes,” Jones wrote in his Facebook post. “Businesses won’t achieve results and could end up doing less business on Facebook if the people they’re connected to aren’t real. It’s in our best interest to make sure that interactions are authentic.”
To fight spam, Jones wrote, Facebook is using machine learning tools to flag suspicious behavior. “When it’s caught, accounts of violators are shut down and fake likes are removed. Facebook also limits the number of likes per account and if a user’s like activity spikes unusually, the company’s spam fighters ask for verification.”
