Enhancing News Authenticity Prediction with Machine Learning Approach - Couverture souple

Mohod, Dr M M ; Chikte, Pranav ; Shrirao, Aditya

9786630040586: Enhancing News Authenticity Prediction with Machine Learning Approach

Couverture souple

ISBN 10 : 6630040589 ISBN 13 : 9786630040586

Editeur : LAP Lambert Academic Publishing, 2026

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�diteur: LAP Lambert Academic Publishing
Date d'�dition: 2026
Langue: anglais
ISBN 10: 6630040589
ISBN 13: 9786630040586
Reliure: Broch�
Nombre de pages: 56
Coordonn�es du fabricant: non disponible
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Enhancing News Authenticity Prediction with Machine Learning Approach (Paperback)

Dr M.M. Mohod

Edit� par LAP Lambert Academic Publishing, 2026

ISBN 10 : 6630040589 ISBN 13 : 9786630040586

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Paperback. Etat : new. Paperback. The rapid proliferation of misinformation across digital platforms poses a critical threat to public discourse, democratic processes, and societal trust. Manual verification systems cannot keep pace with the volume and velocity of fake news being generated, necessitating the development of automated detection mechanisms. This work presents a lightweight machine learning approach for fake news detection using a PassiveAggressive Classifier combined with TF-IDF vectorization, trained and evaluated on the WELFake benchmark dataset comprising 72,119 news articles sourced from multiple platforms spanning 2016 to 2020. The proposed system achieves 96.19% classification accuracy on 14,424 test articles, with precision and recall scores of 0.96-0.97 for both classes and a balanced F1-score of 0.96, validated using a CalibratedClassifierCV wrapper providing calibrated probability outputs. Beyond classification, the system incorporates LIME-based explainability for word-level prediction reasoning, real-time URL verification with source credibility analysis, clickbait detection, and evidence-backed verdict generation using the Gemini API. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N� de r�f. du vendeur 9786630040586

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Enhancing News Authenticity Prediction with Machine Learning Approach

Mohod, M. M.

Edit� par LAP LAMBERT Academic Publishing, 2026

ISBN 10 : 6630040589 ISBN 13 : 9786630040586

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Enhancing News Authenticity Prediction with Machine Learning Approach

Mohod, Dr M M; Chikte, Pranav; Shrirao, Aditya

Edit� par LAP Lambert Academic Publishing, 2026

ISBN 10 : 6630040589 ISBN 13 : 9786630040586

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Enhancing News Authenticity Prediction with Machine Learning Approach

Mohod, M. M.

Edit� par LAP LAMBERT Academic Publishing, 2026

ISBN 10 : 6630040589 ISBN 13 : 9786630040586

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Enhancing News Authenticity Prediction with Machine Learning Approach

M. M. Mohod

Edit� par LAP LAMBERT Academic Publishing Jun 2026, 2026

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 56 pp. Englisch. N� de r�f. du vendeur 9786630040586

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Enhancing News Authenticity Prediction with Machine Learning Approach : Smart News Verification

M. M. Mohod

Edit� par LAP LAMBERT Academic Publishing, 2026

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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The rapid proliferation of misinformation across digital platforms poses a critical threat to public discourse, democratic processes, and societal trust. Manual verification systems cannot keep pace with the volume and velocity of fake news being generated, necessitating the development of automated detection mechanisms. This work presents a lightweight machine learning approach for fake news detection using a PassiveAggressive Classifier combined with TF-IDF vectorization, trained and evaluated on the WELFake benchmark dataset comprising 72,119 news articles sourced from multiple platforms spanning 2016 to 2020. The proposed system achieves 96.19% classification accuracy on 14,424 test articles, with precision and recall scores of 0.96-0.97 for both classes and a balanced F1-score of 0.96, validated using a CalibratedClassifierCV wrapper providing calibrated probability outputs. Beyond classification, the system incorporates LIME-based explainability for word-level prediction reasoning, real-time URL verification with source credibility analysis, clickbait detection, and evidence-backed verdict generation using the Gemini API. N� de r�f. du vendeur 9786630040586

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Enhancing News Authenticity Prediction with Machine Learning Approach (Paperback)

Dr M.M. Mohod

Edit� par LAP Lambert Academic Publishing, 2026

ISBN 10 : 6630040589 ISBN 13 : 9786630040586

Neuf Paperback

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Paperback. Etat : new. Paperback. The rapid proliferation of misinformation across digital platforms poses a critical threat to public discourse, democratic processes, and societal trust. Manual verification systems cannot keep pace with the volume and velocity of fake news being generated, necessitating the development of automated detection mechanisms. This work presents a lightweight machine learning approach for fake news detection using a PassiveAggressive Classifier combined with TF-IDF vectorization, trained and evaluated on the WELFake benchmark dataset comprising 72,119 news articles sourced from multiple platforms spanning 2016 to 2020. The proposed system achieves 96.19% classification accuracy on 14,424 test articles, with precision and recall scores of 0.96-0.97 for both classes and a balanced F1-score of 0.96, validated using a CalibratedClassifierCV wrapper providing calibrated probability outputs. Beyond classification, the system incorporates LIME-based explainability for word-level prediction reasoning, real-time URL verification with source credibility analysis, clickbait detection, and evidence-backed verdict generation using the Gemini API. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N� de r�f. du vendeur 9786630040586

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