Main Reference PaperA Neural Network-Based Ensemble Approach for Spam Detection in Twitter,IEEE Transactions on Computational Social Systems, 2018 [R]
  • An ensemble convolutional neural network(CNN) and feature-based methods are proposed for the task of spam detection at tweet level. By exploiting various word embeddings with different dimensions to detect the spam at tweet level. Each CNN is trained with word embeddings of different dimensions. Then apply the neural network-based meta-classifier is applied to the newly created data set to classify the given tweet to spam or non-spam.

Description
  • An ensemble convolutional neural network(CNN) and feature-based methods are proposed for the task of spam detection at tweet level. By exploiting various word embeddings with different dimensions to detect the spam at tweet level. Each CNN is trained with word embeddings of different dimensions. Then apply the neural network-based meta-classifier is applied to the newly created data set to classify the given tweet to spam or non-spam.

  • To detect the twitter spam is based on ensemble classifier.

Aim & Objectives
  • To detect the twitter spam is based on ensemble classifier.

  • The performance of the deep learning methods can be further improved by considering additional information about the tweets or their authors.

Contribution
  • The performance of the deep learning methods can be further improved by considering additional information about the tweets or their authors.

  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

Project Recommended For
  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

Order To Delivery
  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

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