Year: 2024
Type: article
Abstract: In the contemporary landscape of pervasive socialmedia usage, the identification of fake profiles standsas a crucial element in preserving online security.This research delves into the realm of machinelearning algorithms, focusing on the comparativeanalysis of LightGBM and Support Vector Machine(SVM) for the task of detecting fake accounts onsocial media platforms. Our study harnesses thepower of these two algorithms, both known for theirrobust capabilities, and evaluates their performanceagainst each other. The research utilizes a diverse setof features derived from user profiles, postingbehavior, and linguistic patterns, with NaturalLanguage Processing (NLP) techniques applied toextract nuanced insights from textual content.
Language: English
Topic: Spam and Phishing Detection
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W7216710375