Yapay Zekâ Tabanlı Doğal Dil İşleme Yaklaşımını Kullanarak.

Fake news is fabricated news that spread consciously or unconsciously through various communication channels and has no real share. Today, the masses receive most news on digital and social media. In such communication environments, where news can be transferred to the masses quickly, the accuracy of this news can often be abused. News of unknown origin can cause serious problems in societies by making disinformation or misinformation. Especially, fake news exposed to information pollution in the internet environment can show its effect on society very quickly. To prevent such problems in digital environments, an artificial intelligence-based approach that can grasp the accuracy of the news and confirm it quickly is proposed in this study. In addition, a classification analysis was performed using the Natural Language Processing (NLP) method, a sub-branch of artificial intelligence, to determine whether the news was real or false using the dataset that was accessible. The dataset consisted of 6335 news headlines and content. While 3171 of this news is real news; 3164 is fake news. In the analysis of the study, the Long Short Term Memory (LSTM) model was used together with the NLP method and the training of the dataset was carried out with this model. As a result, the overall accuracy success from the training data was 99.83%, and the overall accuracy success from the test data was 91.48%. These results show us that similar studies that we plan to think about in the future have been promising. [ABSTRACT FROM AUTHOR]