Conspiracy theories, if not debunked initially, possess a strange magnetic power, meaning that once an individual is even mildly swayed by a false narrative, they can get sucked into becoming a full-blown believer in no time. Over a period, such persons can spread the lies to more and more people, creating an army of ignorant minds. Before you know it, such an “infodemic” has infected a larger audience than any virus ever can. The entire 5G-coronavirus theory of 2020 is a fine example of this. In that case, the simpletons who believed that 5G mobile networks created the novel coronavirus were gullible—and foolish—enough to vandalize several telecom towers around the world in an attempt to “end” the pandemic. Therefore, it is imperative to dismantle such theories before the general public is misled.
Machine learning and big data analytics are a few entities through which the posts propagating unfounded theories can be debunked and taken off social media sites, arguably the main source of fake news.
By Testing Established Narratives
Researchers from the University of California (UCLA) have developed a machine learning-based tool to debunk the contentious stories in social media posts and news articles on the web. The system uses web crawlers to draw comparative analysis between the narrative of the post or article and past reference events. Such tools identify narratives based on the characters, places and actions. The relationship between such disparate, real-life elements is assessed to find the role each of them plays within the narrative. For a given narrative to be closer to the truth, it should be solid even if some of the layers involved are removed. In contrast, removing one or two false narratives involving made-up elements would result in the story crumbling to the ground.
By Using Sentiment Analysis
Another study involving big data analytics and sentiment analysis found that a much higher proportion of fake news stories involved negative sentiments, meaning that such posts were created with the purpose of spreading dread amongst the masses. Such posts can then be investigated and taken down from social media pages before several people share or view them. Both these methods use cold, hard data and analytics and a brute-force approach to force fake news out of existence from the web.
The concept of conspiracy theories is as old as spoken or written media itself. While most fake theories are laughably tacky and easy to ignore, there are also some that could tear apart the fabric of society as you know it. Machine learning and big data analytics are handy tools to detect and eliminate such theories from the internet in their initial stages before several others know about them.
