Detected Source-based fake news via Word2vec algorithm
الموضوعات : journal of Artificial Intelligence in Electrical Engineering
Hamid Sharifi Heris
1
(Computer science department, Azad University, Ahar, Iran)
Jafar Sheykhzadeh
2
(Computer science department, Azad University, Ahar, Iran)
الکلمات المفتاحية: Data mining, Machine Learning, Word2Vec, fake news detection,
ملخص المقالة :
today and regarding the increase of social media platforms and the people welcoming these networks has led to share different data throughout the world without the confirmation by the platforms. This has increased the incorrect data frequency and has had great effects on political, economic, and social fields. such incorrect data are called fake news. This has changed into one of the topical issues in today’s society. Through the proposal of an appropriate solution and first through analyzing the news resources in the dataset called BuzzfeedNews, we have concluded that websites with better fames propagate less fake news. We changed the data into vector using Word2vec and investigated the similarity of the taught data and the tagged data in the dataset and got the least precision amounting to 0.60 and the highest precision amounting to 0.94 out of 1 and the results showed that our algorithm has been very helpful in discovering the qualified news.
