Fake news has become a problem for the internet at large. Fake news is generally spread through social media platforms and other internet platforms that are difficult to moderate. The spreading of fake news can lead to misinformation and creating drama over something that is false or otherwise cannot be confirmed.
Platforms like Facebook and Twitter have been criticized for not policing users who actively engage in spreading this type of misinformation. Sometimes those platforms have trouble due to how fast the information is spread. It can be hard to pinpoint where the post or posts started. Twitter is working on a new feature that tags the original poster which would, in theory, give them a starting point.
But now, there might be software coming that could auto-detect fake news on social media platforms. The Fraunhofer Institute is working on such software designed to analyze social media posts analyzing the data within.
As well as processing text, the tool also factors metadata into its analysis and delivers its findings in visual form. “Our software focuses on Twitter and other websites. Tweets are where you find the links pointing to the web pages that contain the actual fake news. In other words, social media acts as a trigger, if you like. Fake news items are often hosted on websites designed to mimic the web presence of news agencies and can be difficult to distinguish from the genuine sites. In many cases, they will be based on official news items, but in which the wording has been altered,” explains Prof. Ulrich Schade of Fraunhofer FKIE, whose research group developed the tool.
Schade and his team begin the process by building libraries made up of serious news pieces and also texts that users have identified as fake news. These then form the learning sets used to train the system. To filter out fake news, the researchers employ machine learning techniques that automatically search for specific markers in texts and metadata. For instance, in a political context, it could be formulations or combinations of words that rarely occur in everyday language or in journalistic reporting, such as “the current chancellor of Germany.” Linguistic errors are also a red flag. This is particularly common when the author of the fake news was writing in a language other than their native tongue. In such cases, incorrect punctuation, spelling, verb forms or sentence structure are all warnings of a potential fake news item. Other indicators might include out-of-place expressions or cumbersome formulations.
“When we supply the system with an array of markers, the tool will teach itself to select the markers that work. Another decisive factorFraunhofer-Gesellschaft
ischoosing the machine learning approach that will deliver the best results. It’s a very time-consuming process,because you have to run the various algorithms with different combinations of markers,” says Schade.
The company says the new software will be able to detect hate speech as well. They say this new software could be useful as an early warning system for companies like Facebook and Twitter. It’s definitely interesting and it will be interesting to see if social media companies actually begin using it. You can read more about it at the source link below.Source: Fraunhofer-Gesellschaft
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