A Review : Fake News Analysis and Detection
DOI:
https://doi.org/10.32628/IJSRSET207319Keywords:
Fake News, Random Forest, Xgboost, Analysis, Detection.Abstract
With the growing world in terms of technology and population, the growth of technological use by the population has also increased. The technology has become a part of every human being’s life. It is not just a part of his professional life but also a part of his personal life. There are so many things happening in the world that keeps the world changing. To grow along with this growing world, we need to keep ourselves updated. Media plays an important role in keeping the population updated. The world is kept updated irrespective of the location of the population reading the news and the location of the incident occurring. Fake news is the biggest drawback in this process. We believe what we see and what we read as it the only way to keep ourselves updated. So Fake news hampers the population and may result in unexpected incidents. So it is the need of the hour to understand the difference between real and fake news. This project is for fake news analysis and detection. A dataset of news is considered, pre processing is done and then the fake news and real news are predicted using random forest and xgboost algorithms.
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