A hybrid classification method for Twitter spam detection based on differential evolution and random forest
Author:
Affiliation:
1. Department of Computer Engineering, Science and Research Branch Islamic Azad University Tehran Iran
2. Department of Computer Engineering, Shahr‐e‐Qods Branch Islamic Azad University Tehran Iran
Publisher
Wiley
Subject
Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.6381
Reference41 articles.
1. KarakaşlıMS AydinMA YarkanS BoyaciA.Dynamic feature selection for spam detection in Twitter. Paper presented at: Proceedings of the International Telecommunications Conference; 2019:239‐250; Springer New York NY.
2. Big data analytics meets social media: A systematic review of techniques, open issues, and future directions
3. Leveraging big data in smart cities: A systematic review
4. Big data analytics in weather forecasting: a systematic review;Fathi M;Arch Comput Methods Eng,2021
5. Detecting spamming activities in twitter based on deep-learning technique
Cited by 29 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. A systematic review of machine learning methods in software testing;Applied Soft Computing;2024-09
2. Ab‐HIDS: An anomaly‐based host intrusion detection system using frequency of N‐gram system call features and ensemble learning for containerized environment;Concurrency and Computation: Practice and Experience;2024-08-06
3. Prediction of Settling Velocity of Microplastics by Multiple Machine-Learning Methods;Water;2024-06-28
4. A novel deep learning model-based optimization algorithm for text message spam detection;The Journal of Supercomputing;2024-05-02
5. Leveraging Sentiment Analysis for Identifying Influential Users in Online Health Communities: A Case Study on the Lung Cancer Survivors Network;2024 1st International Conference on Trends in Engineering Systems and Technologies (ICTEST);2024-04-11
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3