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project title
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demo 2
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demo1
Inspiration
The rise of fake news and misinformation online, making it difficult to discern fact from fiction. The need for tools to empower users to critically evaluate online content and make informed decisions.
What it does
Identifies fake news articles using an LSTM neural network model. Extracts content from webpages using the Beautiful Soup library. Provides a clear classification (credible or fake news) within the extension's interface.
How we built it
Leveraged a Google Chrome extension for seamless integration with user browsing. Employed Beautiful Soup for efficient web scraping of article content. Implemented a trained LSTM neural network model for fake news prediction.
Challenges we ran into
Ensuring the accuracy and effectiveness of the LSTM model in a constantly evolving online landscape. Maintaining user privacy while securely transmitting data between the extension and the backend server.
Accomplishments that we're proud of
Developed a user-friendly extension that empowers critical thinking about online information. Utilized machine learning to address the growing problem of fake news. Created a tool that promotes responsible information consumption.
What we learned
Learned the value of tools like Beautiful Soup for efficiently extracting content from webpages Ongoing effort required to maintain the accuracy of an LSTM model as fake news tactics evolve The project allowed you to explore how machine learning can be applied to tackle real-world problems like misinformation
What's next for Fake News Detector
Explore integrating fact-checking resources to provide users with additional context. Consider expanding compatibility to other web browsers beyond Google Chrome.
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