Twitter Spam Detection Using Word Vector and Binary Classifier-Reference-Cited by-同舟云学术

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Twitter Spam Detection Using Word Vector and Binary Classifier

Published:2023-10-18 Issue: Volume: Page:
ISSN:
Container-title:2023 International Conference on Self Sustainable Artificial Intelligence Systems (ICSSAS)
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Author:

Marimuthu Ramaprabha¹,Muthulingam Gurusigaamani Ayyanar²,S Vinoth N.A.³,Ganesan Sivasathiya⁴,Ponnuchamy Kardeepa²

Affiliation:

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

2. Kalasalingam Academy of Research and Education,Department of Computer science and Engineering,Virudhunagar,India

3. SRM Institute of Science and Technology Kattankulathur,Department of Computing Technologies,Chennai,India

4. Easwari Engineering College, Ramapuram,Department of Artificial Intelligence and Data Science,Chennai,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10330805/10331621/10331861.pdf?arnumber=10331861

Reference21 articles.

1. Experimental Evaluation of Ensemble Learning-Based Models for Twitter Spam Classification

2. SpADe: Multi-Stage Spam Account Detection for Online Social Networks

3. Particle Swarm Optimization on Deep Reinforcement Learning for Detecting Social Spam Bots and Spam-Influential Users in Twitter Network

4. Modified Genetic Algorithm for Feature Selection and Hyper Parameter Optimization: Case of XGBoost in Spam Prediction

5. Push-to-Trend: A Novel Framework to Detect Trend Promoters in Trending Hashtags

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