Using Artificial Intelligence Systems in News Verification: An Application on X

Abstract

The aim of this study is to analyse the relationship between the interaction rates and the number of followers of independent news accounts broadcasting on social network platforms and the types of fake news they publish and the frequency of publishing fake news. In the study, fake news was categorised using qualitative content analysis method. In addition to this, artificial intelligence was used to check the accuracy of news content shared on social networks and to distinguish misleading information. To obtain the data, Chat GPT was utilised and an AI-powered chatbot was developed with the help of algorithms prepared by the researchers to determine the accuracy of the news. The population of the study consists of the accounts practicing social media journalism on the social networking platform X in Türkiye. The sample of the study consists of 6 accounts with the highest interaction selected by purposive sampling method among the accounts that engage in social media journalism on this platform and have the highest interaction. According to the results obtained from the research, a large proportion of the news content shared by accounts practicing social media journalism on the X platform in Türkiye consists of unverifiable news content. In the category of unverifiable news, news is mostly created in the category of “Fabricated” content.