VeriNews: AI-Powered Fake News Detection System

• 

  Home page

• 

  Real news detected

• 

  fake news detected

Inspiration

Misinformation and fake news are growing problems in today’s digital world, especially through social media and online platforms. This inspired us to build a system that can automatically detect whether a news article is real or fake using machine learning techniques.

What it does

VeriNews is an AI-powered fake news detection system that analyzes news text and classifies it as real or fake. It uses Natural Language Processing (NLP) to understand the content and provides a prediction along with a confidence score in real time.

How we built it

I built the project using Python and machine learning libraries such as Scikit-learn and Pandas. The dataset was taken from real-world news sources and preprocessed to remove noise and missing values. I used TF-IDF (Term Frequency–Inverse Document Frequency) to convert text into numerical features and trained a Logistic Regression model for classification. The model was integrated into a Streamlit web application to provide an interactive user interface.

Challenges we ran into

One of the main challenges was handling large datasets and ensuring fast model training within limited time. I also faced issues with file paths and data loading during development. Additionally, making the model both accurate and fast for real-time predictions was a challenge.

Accomplishments that we're proud of

I successfully built a working machine learning model within a short time and integrated it into a user-friendly web application. The system is able to classify news articles in real time and provides confidence scores, making it both functional and informative.

What we learned

We learned how to apply Natural Language Processing techniques in real-world problems, work with datasets, and build machine learning models. We also gained experience in deploying models using Streamlit and presenting our work effectively.

What's next for VeriNews: AI-Powered Fake News Detection System

In the future, we plan to improve the model by using advanced deep learning techniques such as BERT for better accuracy. We also aim to integrate real-time news APIs and expand the system to detect bias and misinformation patterns across multiple sources.

Built With

• pandas
• python
• scikit-learn
• streamlit