Adapting established text representations for predicting review sentiment in Turkish
Natural Language Processing, and specifically Sentiment Analysis are still unexplored topics with respect to Turkish text. A key challenge is to extract meaningful word and paragraph representations. We provide a comprehensive overview on pre-processing and featurization methods for this problem. Our focus is on the inherent difficulties that come with analyzing Turkish real-world data from the e-commerce domain, such as inconsistent spelling or complicated morphological and grammatical structures.