A Collaborative Hybrid Recommendation System With Sentimental Analysis For Rumour Detection
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Abstract
In online social networking rumours play a vital role to judge and decide everything. Rumours and Comments are considered to be the opinions of public but most of the rumours are not true and relevant. In the proposed system a hybrid recommendation system with collaboration of sentimental analysis is introduced for eliminating the fake and unwanted rumours. This collaboration model helps to cluster and classify these types of rumour attacks and form a chain link from these predictions to eliminate the rumour. Furthermore the system also projects a verification model to find whether it is a rumour or not.
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