Algorithms can be useful in detecting fake news, stopping its spread and countering misinformation
Fake news is a complex problem and can span text, images and video.
For written articles in particular, there are several ways of generating fake news. A fake news article could be produced by selectively editing facts, including people's names, dates or statistics. An article could also be completely fabricated with made-up events or people.
Fake news articles can also be machine-generated as advances in artificial intelligence make it particularly easy to generate misinformation.
Damaging effects
Questions like: “Was there voter fraud during the 2020 U.S. elections?” or “Is climate change a hoax?” can be fact-checked by analyzing available data. These questions can be answered with true or false, but there is potential for misinformation surrounding questions like these.
Misinformation and disinformation — or fake news — can have damaging effects on a large number of people in a short time. Although the notion of fake news has existed well before technological advances, social media have exacerbated the problem.
A 2018 Twitter study showed that false news stories were more commonly retweeted by humans than bots, and 70 per cent more likely to be retweeted than true stories. The same study found that it took true stories approximately six times longer to reach a group of 1,500 people and, while true stories rarely reached more than 1,000 people, popular false news could spread up to 100,000.
The 2020 US presidential election, COVID-19 vaccines and climate change have all been the subject of misinformation campaigns with grave consequences. It is estimated that misinformation surrounding COVID-19 costs between USD 50-300 million daily. The cost of political misinformation could be civil disorder, violence or even erosion of
Read more on tech.hindustantimes.com
