| dc.description.abstract | Abstract: Today, false news is easily created
and distributed across many social media
platforms. Due to that, people find it difficult
to choose between right and wrong
information on those platforms. Therefore, a
strong need emerges to develop a factchecking
platform to overcome this problem.
Fact-checking means the process of verifying
information. A CNN, RNN-LSTM based
mobile solution has proposed from this study
to verify information on social media
including many features. CNN, RNN-LSTM
based hybrid model ables to capture the
high-level features and long-term
dependencies from the input text. Some of
the features of the mobile application
includes fact-checking, daily news updates,
news reporting and social media trends etc.
The mobile solution is developed using
Flutter as the front-end framework and
Firebase as the back-end framework
including REST APIs to gather daily news
articles. The hybrid model achieved a 92%
accuracy when checking the information
circulating on social media. | en_US |
