… tweets from non-depressive tweets. … hybrid CNN-biLSTM, RNN, and CNN classification
approach. In this study, depression is predicted via a hybrid CNN-biLSTM approach, using Twitter…

… methods and different deep learning models. We propose a new hybrid deep learning model
… In this study, we used a dataset collected from shared user tweets about a GSM operator in …

… a hybrid deep learning model, called DEA-RNN, to detect CB on Twitter social media
network. The proposed DEA-RNN model combines Elman type Recurrent Neural Networks (RNN) …

… a deeper comprehension of how the public views the illness. This research uses a CNN-LSTM-based
hybrid … introduces a hybrid approach based on CNN and LSTM to identify users' …

… This study uses a hybrid deep learning approach to find user opinion about Monkeypox …
This study uses a hybrid deep learning approach to find user opinion about Monkeypox infection …

… Machine Learning (ML), and Deep Learning (DL) techniques. In this work, the baseline models
and hybrid models of Deep Neural Network … classification of Malayalam tweets as positive…

… based approach for sentiment analysis using text data. POS is … and Deep learning applications.
In this paper, we analyze the tweets of the individual person using hybrid deep learning (…

… user tweets or reasons to make a decision functioning clear or easy to understand, we aim to
develop an explainable deep learning-based approach … user and his posts on social media. …

… posted between October 2019 and May 2020 by 482 users, a significant rise in depressing
tweets was observed between February and May of 2020, which indicates as an impact of the …

… It might lower the success rate of supervised learning. So, our objective is to use a hybrid
of unsupervised Machine Learning (ML) techniques to classify tweets, statistical modeling to …