Hoax Articles and Machine learning

Hoax Articles and Machine learning

What exactly are hoax articles? Hoax is defined as to trick into believing or accepting as genuine something false and often preposterous. These methods are now in trend for spreading fake news and malicious content.

Machine learning is a way to fight such internet traps where artificial intelligence is no less than cops. The basic reason to spread hoax articles is the intention behind it. It can be all about politics or fake publicity stunts to pull attention and to an extent traps to let down celebrities and government.

Such posts multiply themselves leading to trends and also passing on fake information which misleads the social media users on internet and readers of newspaper. Hoax articles are not just related to internet posts, they are also more into journalism.

fake posts on facebook

Also read: Three smartphone myths which are not true

One cannot deny the fact that everything we read is not 100% truth and at the worst case not even 1%.  These articles mostly focus towards spamming of wrong medications, encouraging youth towards anti nationalism and also about downfall of government.

How machine language comes into picture to reduce of Hoax articles on internet?

The problems get simplified when machine learning falls into action. Through machine learning the technical team can target all the spam posts by comparing it with similar posts. Since a comparison takes place the fall of wrong news increases.

For example, Hoax articles about Medical concepts and pharmaceutical information increases on the large scale as it leads to more number of views and spread. Machine learning can compare such articles with more number of similar articles and also compare it with expertise information.

Facebook is the second most which encounters most of such information after Instagram. So, in the recent blog Facebook quotes about its useful implementation of Machine learning to eliminate such articles.

Facebook quoted :

Machine learning helps us identify duplicates of debunked stories. For example, a fact-checker in France debunked the claim that you can save a person having a stroke by using a needle to prick their finger and draw blood. This allowed us to identify over 20 domains and over 1,400 links spreading that same claim.

Although its about the posts that spread the real key behind them is Human intelligence. Such people always look forward to amplify their way of spamming to beat machine learning. People use it to increase the popularity of their content or to become popular. It is always good to understand that everything you read on internet is not 100% truth which is also same to an extent  in the case of Journalism.