aspg-3-3460-1791417763 20261008000243 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Fusion: Practice and Applications FPA 2770-0070 2692-4048 2025 18 1 Hassan Al-Sukhni Cybersecurity Department, Faculty of Science and Information Technology, Jadara University, Irbid, Jordan Qusay Bsoul Cybersecurity Department, College of Computer Sciences and Informatics, Amman Arab University, Amman, Jordan Sharaf Alzoubi Department of Software Engineering , College of Computer Sciences and Informatics, Amman Arab University, Amman, 11953, Jordan Fadi yassin Salem Al jawazneh Faculty of Information Technology, Applied Science Private University, Amman, Jordan 5Misr International University, Cairo, Egypt Dalia Ehab Abdelaziz Misr International University, Cairo, Egypt Hisham Mohamed Gamel BIS Department, Obour High Institute for Management and Informatics, Cairo, Egypt Diaa Salama AbdElminaam MEU Research Unit, Middle East University, Amman, Jordan; Jadara Research Center, Jadara University, Irbid, Jordan News agencies connect global events to local communities. It plays a pivotal role in influencing public opinion. Thus, the necessity arises to recognize news article’s sentiment. The purpose of this paper is to analyze sentiment for English and Arabic news articles in terms of positivity, negativity, or neutrality. Analyzing the articles of Arabic and English news can be challenging from the perspective of morphology. In this paper, we introduce 4 Machine Learning methods, including Logistic Regression (LR), k Nearest Neighbors (KNN), Random Forests (RF) and Naive Bayes (NB), with the TF-IDF as the feature extraction. The study was validated using 2 data sets (BBC, SANAD Arabic news), and two learning models (Hold out and 10-fold cross-validation). The evaluation was based on; Accuracy (ACC), Precision (PREC), Recall (REC), F1-score (F1), and The Matthews Correlation Coefficient (MCC) where it shows an outstanding performance for ML on a 10-fold strategy. The experiments provided in the paper indicated that the proposed ML models achieved the best results. 2025 226 239 3460 https://creativecommons.org/licenses/by/4.0/ 10.54216/FPA.180115 https://www.americaspg.com/journal/3/article/3460 https://www.americaspg.com/storage/41735609015.pdf