2026-04-17T17:42:17.061Z http://ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai

ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai:3:9185 2022-11-18T19:03:13Z 3

COVID-19 Fake News Detection by Improved Ant Lion Optimizer Metaheuristics, Chapter in AIS Algorithms for Intelligent Systems: ICSISCET 2021: Artificial Intelligence and Sustainable Computing, Springer 2022 http://ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai/record/3/9185 https://link.springer.com/chapter/10.1007/978-981-19-1653-3_35 M. Zivkovic N. Bacanin J. Arandjelovic S. Stanojlovic A. Rakic K. Venkatachalam The issue of false news on the Internet is not a new one. In the case of a worldwide epidemic, however, this type of disinformation may be harmful, confusing, and costly in terms of human lives lost. The current COVID-19 epidemic has regrettably resulted in a huge and astonishing dissemination of bogus news, including information about the disease, immunization, and the number of deaths. This study is focused on application of a modified ant lion optimizer, a unique nature-inspired algorithm (ALO). The ALO algorithm replicates the natural antilion’s trapping technique. Wander of ants, constructing traps, trapping of ants in traps, collecting victims, and re-constructing traps represent five basic phases of hunting prey. The modified ALO approach was utilized to enhance the classification accuracy, by feature selection and dimensionality reduction. The ALO was used as a wrapper feature selection. The results from the experiments were compared to the very modern classifiers and other methods that on the same issue, they were utilized. Overall, the simulation results show that the suggested ALO-based technique outperforms the other algorithms in the comparison study in terms of accuracy. bookPart Springer, Singapore 469 484 10.1007/978-981-19-1653-3_35 AIS Algorithms for Intelligent Systems: ICSISCET 2021: Artificial Intelligence and Sustainable Computing