FAKE NEWS DETECTION ON KAGGLE DATASETS USING DECISION TREE ALGORITHM
G. Priyanka
, N. Nandhini Sai , Poojakaran D , Subalakshmi R , Sneha R
Fake news detection, logistic regression, decision tree, random forest, gradient boosting, TF-IDF Vectorizer, Machine learning.
Today, social media is widely used to disseminate real-time news. Users of social media are scattered over a wide range of people and do not belong to any one age or gender category. This is due to the fact that it is simple to transmit, spreads quickly, is simple to access, and costs little to spread the word. Social media users are utilising it to disseminate fake news, and malicious information for purposes of commerce, politics, and entertainment. This dissertation offered four approaches to use in judging the veracity of the news, so limiting its dissemination, to address these challenges. The sharing of information via the internet has been increasing over the years. The internet has been a source of easy information and is used more than traditional ways like newspapers or magazines. It is important to identify information from the internet as real or fake as misleading information could cause a lot of havoc in society. Fake information can be the cause of riots, and chaos and can affect a large group of society. In this paper,the methodology used to detect false news using machine learning classifiers to authenticate whether the news is real or not. For the generation of feature vectors, TF-IDF Vectorizer have been utilized.
"FAKE NEWS DETECTION ON KAGGLE DATASETS USING DECISION TREE ALGORITHM", TIJER - TIJER - INTERNATIONAL RESEARCH JOURNAL (www.TIJER.org), ISSN:2349-9249, Vol.11, Issue 2, page no.466-471, February-2024, Available :https://tijer.org/TIJER/papers/TIJERB001072.pdf
Volume 11
Issue 2,
February-2024
Pages : 466-471
Paper Reg. ID: TIJER_151083
Published Paper Id: TIJERB001072
Downloads: 000284
Research Area: Science and Technology
Country: Tiruvallur, Tamil Nadu, India
ISSN: 2349-9249 | IMPACT FACTOR: 8.57 Calculated By Google Scholar | ESTD YEAR: 2014
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.57 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: TIJER (IJ Publication) Janvi Wave
