首页|New Machine Learning Findings from King Saud University Published (The Effect of Feature Selection on the Accuracy of Xplatform User Credibility Detection with Supervised Machine Learning)
New Machine Learning Findings from King Saud University Published (The Effect of Feature Selection on the Accuracy of Xplatform User Credibility Detection with Supervised Machine Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Researchers detail new data in artificial intelligence. According to news reporting outof Riyadh, Saudi Arabia, by NewsRx editors, research stated, “In the era of digital information, onlineplatforms play a crucial role in shaping public opinion.”Financial supporters for this research include Ministry of Education in Saudi Arabia.Our news correspondents obtained a quote from the research from King Saud University: “However,the extensive spread of misinformation and fake news poses a significant challenge, largely fueled by noncredibleusers. Detecting user credibility is vital for ensuring the reliability of information on these platforms.This study employs supervised machine learning algorithms, leveraging key user features to enhance credibilitydetection. Feature selection methods, specifically SelectKBest and correlation-based algorithms,are explored for their impact on X-Platform user credibility detection. Utilizing various classifiers, includingsupport vector machine, logistic regression, and XGBoost, experiments are conducted on the ArPFNdataset, which is a labeled, balanced, publicly available dataset. The evaluation includes measures likeaccuracy, precision, recall, and F1-score to assess efficiency.”
King Saud UniversityRiyadhSaudi ArabiaAsiaCyborgsEmerging TechnologiesMachine Learning
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