- Tytuł:
-
Weighted accuracy algorithmic approach in counteracting fake news and disinformation
Algorytmiczne podejście do dokładności ważonej w przeciwdziałaniu fałszywym informacjom i dezinformacji - Autorzy:
- Bonsu, K.O.
- Powiązania:
- https://bibliotekanauki.pl/articles/2048986.pdf
- Data publikacji:
- 2021
- Wydawca:
- Akademia Bialska Nauk Stosowanych im. Jana Pawła II w Białej Podlaskiej
- Tematy:
-
artificial intelligence
natural language processing
machine learning algorithm
disinformation
digital revolution
fake news - Opis:
- Subject and purpose of work: Fake news and disinformation are polluting information environment. Hence, this paper proposes a methodology for fake news detection through the combined weighted accuracies of seven machine learning algorithms. Materials and methods: This paper uses natural language processing to analyze the text content of a list of news samples and then predicts whether they are FAKE or REAL. Results: Weighted accuracy algorithmic approach has been shown to reduce overfitting. It was revealed that the individual performance of the different algorithms improved after the data was extracted from the news outlet websites and 'quality' data was filtered by the constraint mechanism developed in the experiment. Conclusions: This model is different from the existing mechanisms in the sense that it automates the algorithm selection process and at the same time takes into account the performance of all the algorithms used, including the less performing ones, thereby increasing the mean accuracy of all the algorithm accuracies.
- Źródło:
-
Economic and Regional Studies; 2021, 14, 1; 99-107
2083-3725
2451-182X - Pojawia się w:
- Economic and Regional Studies
- Dostawca treści:
- Biblioteka Nauki
Artykuł