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Statistics report
Feb. 2024
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 132
Paper Published : 1541
No. of Authors : 4000
  Journal Paper


Paper Title :
Comparative Analysis Of Classification Algorithms For Social Media Misinformation

Author :Shagufta Khan, Rupal Snehkunj

Article Citation :Shagufta Khan ,Rupal Snehkunj , (2022 ) " Comparative Analysis Of Classification Algorithms For Social Media Misinformation " , International Journal of Advance Computational Engineering and Networking (IJACEN) , pp. 40-43, Volume-10,Issue-9

Abstract : Abstract- Misinformation dissemination on social media platforms has seen a surge in the last few years, leading to severe consequences for individuals and society. It is crucial to determine if the information consumed on social media platforms isreal or fabricated. The proposed study demonstrates a few methodologies to identify false information from real one utilizing Machine learning(ML) classifiers and Natural language processing(NLP) techniques.To determine the best model, a comparison is done between ML classifiers using performance evaluation measures such as Confusion Matrix, Accuracy, Precision, F1-score, and Recall. Further, for feature engineering techniques like CountVectorizer, TF-IDF are employed. Keywords - Machine learning, Social Media Misinformation Classification, Machine Learning Classifiers, Feature Engineering, Fake News on Social Media

Type : Research paper

Published : Volume-10,Issue-9


DOIONLINE NO - IJACEN-IRAJ-DOIONLINE-19043   View Here

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