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Synopsis
It's no secret that social media platforms are proliferating at an unprecedented rate, and with internet access becoming increasingly ubiquitous, the dissemination of fake news has become a swift and effortless process. The ramifications of this phenomenon are profound, particularly in the realms of politics and education, where the impact of fake news can be significantly disruptive.In this research study, we will be using Natural Language Processing (NLP) to transform text- based news headlines into numerical vectors. We examined and contrasted two NLP methods, Bag of Words (BoW) and Term Frequency-Inverse Document Frequency (TF-IDF), to see how well they perform while using different ML algorithm to identify fake news.We will be using several machine learning classification algorithms, including Naïve Bayes, Logistic Regression, Random Forest, and Support Vector Machine. Our aim was to identify the most effective NLP technique for identifying fake news.
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Detecting Fake News: NLP and Machine Learning in Action
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Detecting Fake News
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Detecting Fake News: NLP and Machine Learning in Action
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Detecting Fake News: NLP and Machine Learning in Action
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Detecting Fake News: NLP and Machine Learning in Action
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LAP LAMBERT Academic Publishing Jan 2025, 2025
ISBN 10: 6208421322
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -It's no secret that social media platforms are proliferating at an unprecedented rate, and with internet access becoming increasingly ubiquitous, the dissemination of fake news has become a swift and effortless process. The ramifications of this phenomenon are profound, particularly in the realms of politics and education, where the impact of fake news can be significantly disruptive.In this research study, we will be using Natural Language Processing (NLP) to transform text- based news headlines into numerical vectors. We examined and contrasted two NLP methods, Bag of Words (BoW) and Term Frequency-Inverse Document Frequency (TF-IDF), to see how well they perform while using different ML algorithm to identify fake news.We will be using several machine learning classification algorithms, including Naïve Bayes, Logistic Regression, Random Forest, and Support Vector Machine. Our aim was to identify the most effective NLP technique for identifying fake news.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 52 pp. Englisch. Seller Inventory # 9786208421328
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Detecting Fake News: NLP and Machine Learning in Action
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LAP LAMBERT Academic Publishing, 2025
ISBN 10: 6208421322
ISBN 13: 9786208421328
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - It's no secret that social media platforms are proliferating at an unprecedented rate, and with internet access becoming increasingly ubiquitous, the dissemination of fake news has become a swift and effortless process. The ramifications of this phenomenon are profound, particularly in the realms of politics and education, where the impact of fake news can be significantly disruptive.In this research study, we will be using Natural Language Processing (NLP) to transform text- based news headlines into numerical vectors. We examined and contrasted two NLP methods, Bag of Words (BoW) and Term Frequency-Inverse Document Frequency (TF-IDF), to see how well they perform while using different ML algorithm to identify fake news.We will be using several machine learning classification algorithms, including Naïve Bayes, Logistic Regression, Random Forest, and Support Vector Machine. Our aim was to identify the most effective NLP technique for identifying fake news. Seller Inventory # 9786208421328