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Research Proposal on User Credibility Detection in Social Networks using Deep Learning Models

   User credibility is an important feature in information technology, mainly focusing on the quality and believability of the information. User credibility helps to identify the untrue information shared on social media. User credibility detection aims to recognize accurate and reliable users based on their shared information. User credibility detection in social media is a challenging task due to the untrue information shared rapidly by random or unknown users. User credibility is detected by analyzing and verifying the sources, content, and environment information shared in social media.
   Deep learning models have the potential to handle heterogeneous data from social media and automatically learn task-specific features from such data. Deep neural networks extract the inherent features from the data to effectively recognize the credibility of the user. User credibility detection address the main features of the user data in the social network by incorporating deep neural networks.