The many faces of Fake News

Emergent Methods
3 min readJun 28, 2024

If you believe the critics on the Internet, the world is plagued by a new problem called Fake News that makes trusting news difficult. But this issue of “fake news” essentially dates back to the first days of humanity when one person reported to another about an event. There was never a time that journalism was free of accusations of the concept of fake news, although the words used to describe the problem have varied: Muckraking, favoritism, libel, hack-job, political spin, and so forth.

The specific term “fake news,” has been around for centuries, but only more recently took its place as the most popular way to describe news that people Just Don’t Like. It’s a pejorative term, the popularity of which has boomed with the Internet, and it has been used interchangeably to describe literally dozens of types of news reports, including satire, honest errors, amateurish writings, publicity stunts, etc. The Fake News description is casually applied to the entire body of any news story with even the slightest single error of fact: A misplaced decimal point, a misspelled name, a mis-titled business executive, etc.

And of course, accusations of Fake News often extend into accusations of Fake Journalist, Fake Newspaper, and even Fake Media.

A blindfolded person reading a newspaper that is on fire.
Photo by Max Muselmann on Unsplash.

In our main essay about transparency in the media, “Transparency in News Reporting”, we refer to ways that readers and viewers can improve transparency for themselves, and one of those tools is “education.” We believe that an education into the “fake news” phenomenon can provide a healthy starting point.

You might not like the news you are hearing; but accurate, objective news, however painful, can provide great benefit and help you make important decisions. To call it fake news, and to use that misnomer as an excuse to dismiss the news, is a head-in-the-sand approach to life. Yet, increasing numbers of people are engaging in this escapism, prompted perhaps by some select gaslighting world leaders.

Prior to the industrial revolution, influences upon public sentiment were essentially limited to single-person efforts such as speeches and hand-written messages sometimes posted to marketplaces. Technological developments such as the printing press, radio and television increasingly made bigger audiences more easily accessible to greater numbers of “fringe” or untrained journalists. As media outlets increased in availability and effectiveness, those outlets became increasingly more difficult for critics to monitor. Of course, the Internet with the advent of social media hugely expanded that challenge. Now we have essentially millions of “reporters” littering the globe with conspiracy theories, careless errors, and even outright denials of fact. No, sorry, the world is not flat. It just isn’t.

Transparent marble reflecting land and sky during sunset.
Photo by Louis Maniquet on Unsplash.

Compounding the problem, consumers of that “fake news” blithely pass it along in the form of a “share.” A simple touch of the button, and the chaos continues.

Some of this misinformation is malicious, some downright evil (as when Internet users create fake news to try to affect elections). Some fake news is designed as entertainment. The Onion is an example of “fake news” applauded by some audiences but reviled by others. “O.J. Simpson Allowed to Remain Living After Coffin Doesn’t Fit!” If that headline is “fake,” it’s only in the broadest sense of the word. And if “fake” is bad, it’s only because some readers Just Don’t Like It.

Se how can we deal with fake news? One word — Transparency. Knowing where the news comes from, who reported on the events, and what was their agenda is a silver bullet for battling fake news. Sounds easy, but unfortunately it is not. Read more about Transparency in News Reporting here.

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Emergent Methods
Emergent Methods

Written by Emergent Methods

A computational science company focused on applied machine learning for real-time adaptive modeling of dynamic systems.

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