Fusion: Practice and Applications FPA 2692-4048 2770-0070 10.54216/FPA https://www.americaspg.com/journals/show/3460 2018 2018 Cybersecurity Department, Faculty of Science and Information Technology, Jadara University, Irbid, Jordan admin admin Cybersecurity Department, College of Computer Sciences and Informatics, Amman Arab University, Amman, Jordan Qusay Bsoul Department of Software Engineering , College of Computer Sciences and Informatics, Amman Arab University, Amman, 11953, Jordan Sharaf Alzoubi Faculty of Information Technology, Applied Science Private University, Amman, Jordan 5Misr International University, Cairo, Egypt Fadi yassin Salem Al jawazneh Misr International University, Cairo, Egypt Dalia Ehab Abdelaziz BIS Department, Obour High Institute for Management and Informatics, Cairo, Egypt Hisham Mohamed Gamel MEU Research Unit, Middle East University, Amman, Jordan; Jadara Research Center, Jadara University, Irbid, Jordan Diaa Salama AbdElminaam 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 2025 226 239 10.54216/FPA.180115 https://www.americaspg.com/articleinfo/3/show/3460