التفاصيل البيبلوغرافية
| العنوان: |
Fake News and Breaking News Detection using Machine Learning |
| المؤلفون: |
Arya Sasi, Merin Chacko |
| المصدر: |
(NCECA)-2022, National Conference on Emerging Computer Applications (NCECA)-2022, India, 15 June 2022 |
| بيانات النشر: |
Amal Jyothi College of Engineering Kanjirappally, Kottayam |
| سنة النشر: |
2022 |
| المجموعة: |
Zenodo |
| مصطلحات موضوعية: |
fake news, real news, Machine learning, Naive bayes classifier, Stopwords, TF-IDF vectorizer |
| الوصف: |
— Because of developments in communication and social media, fake news is spreading at a quick and rising rate. Fake news and breaking news identification is a relatively young subject of study that has sparked considerable attention. Due of a scarcity of resources, such as datasets and processing and analysis methodologies, it confronts various difficulties. In this study, we show how a machine learning-based system can recognise false news and breaking news. We used term frequency x0002 inverse document frequency (TF-IDF) of bag of words and n-grams as a feature extraction approach and Naive Bayers as a classifier.In order to train the suggested system, we additionally present a dataset of false and real news. The system's effectiveness is demonstrated by the produced outcomes. |
| نوع الوثيقة: |
conference object |
| اللغة: |
unknown |
| Relation: |
https://zenodo.org/communities/amaljyothi; https://doi.org/10.5281/zenodo.6937310; https://doi.org/10.5281/zenodo.6937311; oai:zenodo.org:6937311 |
| DOI: |
10.5281/zenodo.6937311 |
| الاتاحة: |
https://doi.org/10.5281/zenodo.6937311 |
| Rights: |
info:eu-repo/semantics/openAccess ; Creative Commons Attribution 4.0 International ; https://creativecommons.org/licenses/by/4.0/legalcode |
| رقم الانضمام: |
edsbas.82469900 |
| قاعدة البيانات: |
BASE |