… explain the predictions of recurrent neural networks (RNNs), in particular of LSTMs. The goal
of these methods is to understand the network’… the negation in sentiment analysis reflect in …

… for the improvement in understanding the sentiments, we … a sequence bringing about the
prediction of childhood [24]. … used recursive neural networks to perform sentiment analysis …

… recurrent neural networks (RNNs) are more common in text … strength detection, and offered
more accurate explanation and … network with one hidden layer to predict emotion categories. …

… deep neural network architectures for sentiment analysis. The … convolutional recurrent neural
network architecture with … class are accurately predicted out of the total predicted patterns. …

… experiments is explained in detail in subsequent sections. … approaches are based on
Recurrent Neural Network (RNN), … of sentiment classes and v ̂ is the predicted probability of …

… studies of sentiment analysis systematically and explain the … The cross-domain analysis
predicts the sentiment of a target … combined with a Recurrent Neural Network in this study. …

… recurrent neural network with long short-term memory units to train the Thompson Reuters
News Archive Data from 2003 to 2012, and we test the forecasting … As we explain in Sect. 3.4, …

… plays an important role in better understanding customer/… the predicted scores of these two
models, to infer the sentiment … LSTM [31] is a popular recurrent neural network architecture for …

… not the whole text as input, and LSTM to predict valence-arousal … The explanation may be
that SinaWeibo has broader topics … recurrent neural network model called AEC-LSTM, for text …

… understanding of network public opinion. The technology of … CBOW model predicts target
words based on context … In the traditional recurrent neural network model and LSTM model, …