This report investigates Twitter spam detection using machine learning algorithms. It addresses the challenge of identifying spammers and fake messages on the platform. The study utilizes …

Jan 1, 2020 · The main aim of this research paper is to enhance the efficiency of hacker detection for the Twitter platform using the complex networks technique with adapted machine learning …

Apr 15, 2022 · Performing sentiment analysis on these posts can help us in solving this problem effectively. The main purpose of this proposed work is to develop a system that can determine …

To avoid this spam messages we propose a methodology by us using machine learning algorithms. To develop our approach used a set of content based features. In spam detection …

Saleh beyt sheikh ahmad, Mahnaz rafie and et al.,[1] had proposed the system for Spam detection on twitter using support vector machine and users features by identifying their …

spammers find ways to bypass the spam detection systems by changing their spam posting behaviour. This study focuses on a comparative analysis of six machine learning classifiers, …

Twitter and the academic community have been working on a number of spam detection systems using different machine-learning algorithms in order to safeguard users.

This paper reviews recent studies in the literature that tackled the Twitter spam accounts problem based on machine learning (ML). It then introduces an empirical study to test several ML …

The work has been evaluated with three different machine learning algorithms namely - Support Vector Machine, Neural Network, Random Forest. With Naive Bayes classifier, about 80% of …

Apr 16, 2020 · In this paper, we bridge the gap by proposing a near real-time Twitter spam detection system, which provides near real-time tweets data acquisition, light-weight features …