Abstract:
"
Reading Newspapers is the best way for kids to learn a language and get
information about what is going on in our local communities and globally. Because of
the exponential growth of the Internet and information technology, reading online
news feeds via browsing the Internet has become very common. However, the central
problem of the online newspaper is, it carries negative and violent articles. In this
research project, the author attempts to filter out these negative and unsuitable articles
for children’s reading. By doing so kids only read positively written news articles that
ensure their positive emotional state.
The Tamil News filtering with Aspect-based Sentiment Analysis for Children
system will be a novel system which has not been created ever before and compared
to the existing similar sentiment analysis systems this system outperforms in terms of
accuracy. This system built with Python as its primary language and BERT model is
developed as the core model. This system aims to collect live news articles and
predict the sentiment polarity on those news articles using RSS link."
