The increase in the amount of content shared on social media makes it difficult to extract meaningful information from scientific studies. Accordingly in recent years researchers have been working extensively on sentiment analysis studies for the automatic evaluation of social media data. One of the focuses of these studies is sentiment analysis on tweets. The more tweets are available the more features in terms of words exist. This leads to the curse of dimensionality and sparsity resulting in a ...