RELIANCE: Reliable Ensemble Learning for Information and News Credibility Evaluation

arXiv:2401.10940v2 Announce Type: replace-cross
Abstract: In the era of information proliferation, discerning the credibility of news content poses an ever-growing challenge. This paper introduces RELIANCE, a pioneering ensemble learning system designed for robust information and fake news credibility evaluation. Comprising five diverse base models, including Support Vector Machine (SVM), naive Bayes, logistic regression, random forest, and Bidirectional Long Short Term Memory Networks (BiLSTMs), RELIANCE employs an innovative approach to integrate their strengths, harnessing the collective intelligence of the ensemble for …

abstract arxiv challenge cs.cl cs.ir cs.lg cs.si diverse ensemble evaluation ever fake fake news five information machine paper reliance robust support svm type vector