Sainath Gannarapu, A. Dawoud, Rasha S. Ali, Ali A. Alwan
{"title":"Bot Detection Using Machine Learning Algorithms on Social Media Platforms","authors":"Sainath Gannarapu, A. Dawoud, Rasha S. Ali, Ali A. Alwan","doi":"10.1109/CITISIA50690.2020.9371778","DOIUrl":null,"url":null,"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.","PeriodicalId":145272,"journal":{"name":"2020 5th International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 5th International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CITISIA50690.2020.9371778","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.