Experimental Evaluation of Ensemble Learning-Based Models for Twitter Spam Classification-Reference-Cited by-同舟云学术

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

Published:2022-11-01 Issue: Volume: Page:
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Container-title:2022 5th Information Technology for Education and Development (ITED)
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Author:

Jimoh R. G.¹,Oyelakin A. M.²,Olatinwo I. S.³,Obiwusi K. Y.⁴,Muhammad-Thani S.⁵,Ogundele T. S.⁶,Giwa-Raheem A.⁷,Ayepeku O. F.⁸

Affiliation:

1. University of Ilorin,Department of Computer Science,Ilorin,Nigeria

2. Al-Hikmah Unirsity,Department of Computer Science,Ilorin,Nigeria

3. Federal Polytechnic,Department of Computer Science,Offa,Nigeria

4. Summit University,Department of Mathematics and Computer Science,Offa,Nigeria

5. Kwara State College of Education,Department of Computer Science,Ilorin,Nigeria

6. Al-Hikmah University,Department of Computer Science,Ilorin,Nigeria

7. Centre for Part Time and Professional Studies, Al-Hikmah University,Ilorin,Nigeria

8. Thomas Adewunmi University,Department of Computer Science,Oko,Nigeria

Publisher

IEEE

Link

Reference14 articles.

1. Ensemble Learning;brown;Encyclopedia of Machine Learning,2010

2. Random Forests;breiman;Machine Learning,2001

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2. Extreme Learning Machine for Spammer Detection and Fake User Identification from Twitter;2024 IEEE 13th International Conference on Communication Systems and Network Technologies (CSNT);2024-04-06

5. Twitter Spam Detection Using Word Vector and Binary Classifier;2023 International Conference on Self Sustainable Artificial Intelligence Systems (ICSSAS);2023-10-18