Truth Seeker for Social Media Real or Fake Content
M Ramaraju,
M. Divya,
N. Abhishekitha,
P. Uday,
P. Vidyadhar
In the modern digital era, social media is a major platform for sharing both true and false information,
leading to confusion and panic due to the rapid spread of fake news. The Truth Seeker project aims to
address this issue by developing an intelligent Java-based system that identifies and classifies social
media content as real or fake. It focuses on creating a large ground truth dataset, mainly sourced from
platforms like Twitter, and provides a web-based application for automated detection.The system uses
Java technologies with features such as user registration, dataset uploads through Excel, and SHA-1
hashing for data integrity. It includes interactive dashboards for visualizing data and follows a multitier
architecture using JSP. Technologies like Apache POI, JDBC, and Bootstrap are integrated for
efficient processing, database connectivity, and responsive design. Security is ensured through prepared
statements and AES encryption, while the dataset contains attributes like post ID, title, content, and
labels to support accurate content classification and machine learning and Security is strengthened
using prepared statements to prevent SQL injection and AES encryption for sensitive data, achieving
a high level of protection. Interactive dashboards visualize post distribution, showing trends such as
fake content spreading faster than real content by up to 70%, helping users and administrators make
informed decisions and improve the accuracy of fake news detection systems.
