Sentiment Analysis Label Distribution
For training, close to equal distributed data will give you better results. 

Type of data that you have, generally produced a biased model towards "neutral" class.

Are there any ways to deal with such problem?

I generally perform oversampling of the minority classes, such that for training(only),  have sufficient uniform count of data set.
 SMOTE, ADASYN are the few techniques of oversampling.