Identification of Fake and Spam Users on Social Networking Platforms-Reference-Cited by-同舟云学术

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Identification of Fake and Spam Users on Social Networking Platforms

Published:2023-12-14 Issue: Volume:11 Page:1-5
ISSN:
Container-title:2023 Intelligent Computing and Control for Engineering and Business Systems (ICCEBS)
language:
Short-container-title:

Author:

Rajesh G¹,Kalaivani K Priya²,Hemalatha D¹,Prabhu V³,Siva Rama Lingham N¹

Affiliation:

1. Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology,Department of Computer Science and Engineering,Chennai,India

2. Jeppiaar Engineering College,Department of Computer Science and Engineering,Chennai,India

3. R.M.K Engineering College,Department of Computer Science and Engineering,Chennai,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10447018/10448515/10449109.pdf?arnumber=10449109

Reference21 articles.

1. Statistical Features-Based Real-Time Detection of Drifted Twitter Spam

2. Detecting spam tweets in Twitter using a data stream clustering algorithm

3. A survey on behaviors exhibited by spammers in popular social media networks

4. Twitter analysis for real-time malware discovery

5. $1.00 per RT #BostonMarathon #PrayForBoston: Analyzing fake content on Twitter

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