Datta Dhebe

Automatic Rumour Detection Based On User’s Behaviour Using Autoencoder

Rumors spread on Online Social Networks sometimes can lead to serious social issues. To accurately identify them from normal posts is proved to be of great value. Users behaviors are different when they post rumors and normal posts. Since rumors only account for a small percentage of all posts, they can be regarded as anomalies. Therefore, we propose an anomaly detection method based on autoencoder to perform rumor detection. In this paper we propose several selfadapting thresholds which can facilitate rumor detection. In addition, we further discuss how the different number of hidden layers of autoencoder can influence the detection performance. The experimental results show that there model achieves a good F1 and a low false positive rate.

Army weapon system

Build a weapon Managment system using Netbeans java in front end and in backend use sql for database managment

Message Broadcasting Portal for Colleges

Build a Notice delivery system for a college so that student dont get disturd during lectures when notice come while in a middle of lecture