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Explainable Twitter bot detection model for limited feature:

, In: International Conference on Green Energy, Computing and Intelligent Technology (GEn-CITy 2023),

Javed, D. ; Jhanjhi, N. Z. ; Khan, N. A. - p. None , 2023

Link: https://doi.org/10.1049/icp.2023.1822

RT 
T1 <cTitle>International Conference on Green Energy, Computing and Intelligent Technology (GEn-CITy 2023)</cTitle>: T1 <Title>Explainable Twitter bot detection model for limited features</Title>

UL https://suche.suub.uni-bremen.de/peid=ieee-10269174&Exemplar=1&LAN=DE
				
A1 Javed, D.
A1 Jhanjhi, N. Z.
A1 Khan, N. A.
YR 2023
K1 feature extraction
K1 game theory
K1 learning (artificial intelligence)
K1 politics
K1 sentiment analysis
K1 social networking (online)
K1 AI-driven bot detection technologies
K1 annotated Twitter data
K1 bot categorization
K1 explainable AI-based machine learning approach
K1 explainable twitter bot detection model
K1 feature significance
K1 malicious information
K1 ML model predictions
K1 online discussions
K1 open human conversation
K1 partially automated accounts
K1 public sentiment
K1 SHAP
K1 Shapley additive explanations
K1 Twitter bots
SP None
LK http://dx.doi.org/https://doi.org/10.1049/icp.2023.1822
DO https://doi.org/10.1049/icp.2023.1822
SF ELIB - SuUB Bremen

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