engleski

The Role of Metadata in Fake News Detection

Global technological progress has created the infrastructure for the new type of society and for various media outlets. The phenomenon of fake news is a result of unreliable media outlets and individuals with motives to cause distress, misinformation and disinformation. Fake news can be defined as false and unreliable information which appears trustworthy, but there is no editorial process nor truth behind creating and disseminating it. Fake news can also refer to news satire and parodies, manipulation of photographs and video materials, etc. Technological progress enables “doctoring” of images and texts with the use of sophisticated software. Fake news is easily accessible, especially via social media which then quickly disseminates false narratives and information. The question which poses itself is how to recognize altered or completely fabricated pieces of information. There are multiple possibilities of fake news detection. First of all, there is critical thinking and media literacy but certain fake news is hard to recognize just by using those skills. Having knowledge about data structure, digital objects and metadata can be an answer for recognizing authentic content. Understanding authenticity as well as reliability and integrity can prove useful in enhancing critical thinking, media literacy and an ability to discern fake from real news. It is important to understand that when a certain digital object is authentic it does not mean that it is real and vice versa. The purpose of this paper is to showcase the importance of authentic content and skills with which fake news can be discovered.

fake news ; fake news detection ; digital object ; metadata

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