Bot Detection Using Machine Learning Algorithms on Social Media Platforms

Sainath Gannarapu, A. Dawoud, Rasha S. Ali, Ali A. Alwan
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引用次数: 3

Abstract

Using bots in social media is a significant concern for information validity and authenticity. Currently, there are several solutions for bots detection. However, the accuracy of the detection still needs improvement. The main aim of this paper is to introduce an automatic mechanism for the detection and removal of bots that exist on social media platforms. The research has the purpose of removing the non-genuine accounts, their related information, and the data which are posted by them and to make these platforms free of misleading information. Bots detection and removal will increase the authenticity of the contents presented on different social media platforms. Also, It will improve the level of privacy and authenticity of these platforms and related users. The research uses the bot detection technique based on machine learning algorithms. The components of the study are data, feature selection, and bot detection. The research performs web development and hosting on the collected data with a machine-learning algorithm to perform bot detection in social media networks. The proposed system provides a more accurate and effective system for bot detection using machine learning. The research utilizes various approaches and mechanisms that lead to the enhanced efficiency of bot detection and removals.
在社交媒体平台上使用机器学习算法进行机器人检测
在社交媒体上使用机器人是信息有效性和真实性的重要问题。目前,机器人检测有几种解决方案。然而,检测的准确性仍有待提高。本文的主要目的是引入一种自动机制,用于检测和删除存在于社交媒体平台上的机器人。研究的目的是清除非真实账户及其相关信息,以及他们发布的数据,使这些平台免于误导信息。机器人的检测和移除将提高不同社交媒体平台上呈现内容的真实性。同时,将提高这些平台和相关用户的隐私和真实性。该研究使用了基于机器学习算法的机器人检测技术。该研究的组成部分是数据、特征选择和机器人检测。该研究使用机器学习算法对收集的数据进行网络开发和托管,以在社交媒体网络中执行机器人检测。该系统为机器人检测提供了一个更准确、更有效的机器学习系统。该研究利用了各种方法和机制,从而提高了机器人检测和清除的效率。
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