Learning textual features for Twitter spam detection: A systematic literature review-Reference-Cited by-同舟云学术

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Learning textual features for Twitter spam detection: A systematic literature review

Published:2023-10 Issue: Volume:228 Page:120366
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Bazzaz Abkenar Sepideh,Haghi Kashani Mostafa,Akbari Mohammad^ORCID,Mahdipour Ebrahim

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference134 articles.

1. Detection of Malicious URLs in Twitter;Abhijith,2021

2. Big data analytics meets social media: A systematic review of techniques, open issues, and future directions;Abkenar;Telematics and Informatics,2020

3. Twitter spam account detection based on clustering and classification methods;Adewole;The Journal of Supercomputing,2018

4. Twitter spam account detection based on clustering and classification methods;Adewole;The Journal of Supercomputing,2020

5. Spam filtering of bi-lingual tweets using machine learning;Afzal,2016

Cited by 2 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. Enhancing detection of malicious profiles and spam tweets with an automated honeypot framework powered by deep learning;International Journal of Information Security;2023-12-27

2. Early Malware Characterization based on Online Social Networks;2023 6th International Conference on Advanced Communication Technologies and Networking (CommNet);2023-12-11

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