Facebook has revealed that they are improving their technological measures which will provide brands and pages on the Facebook with “real likes”. The social media giant has stepped up its battle against spammers who are assuring their clients to deliver “likes.”.
In addition to it, Facebook proclaimed that, “We have obtained nearly $2 billion in legal judgments against spammers, and we utilize these channels when possible to remind would-be offenders that we will fight back to prevent abuse on our platform,” according to a blog post from Matt Juneau Facebook integrity engineer. “We also limit likes per account to make spammers’ operations less efficient.”
Most demanding users, including politicians and e-commerce companies, are buying likes to make them appear more popular. Moreover, it is targeting a cottage industry which seeks to deliver these results to Facebook members, often promising “10,000 likes” or more for a fee.
“We have a strong incentive to aggressively get rid of fake likes because businesses and people who use our platform want real connections and results, not fakes,” said the blog 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.”
“It’s important to remember that fraudulent activity is bad for everyone — including page owners, advertisers, Facebook and people on our platform,” he said. “”As our tools have become more sophisticated, we’ve contributed some of our spam-fighting technology to the academic community as well, in hopes of helping other companies combat similar problems.”
The blog also covers the information that the Facebook Inc. partners with other networks where such activity is observed and lends its expertise and insight at uncovering these incidents to academic communities in particular.
Facebook Inc. has already partnered with some other network firms that will allow the social networking giant to be more specific about user behavior.