The aim of this research is to provide a full explanation of a sentiment analysis executed on the "food.com" dataset. The "notebook" folder contains all the information and explanation provided as Jupyter Notebooks. Since the dataset provides the ratings of the users it is possible to train a supervised analysis. Furthermore in the notebook, it's provided the results of different algorithms and models applied on same datasets and compared with some State-of-art models (Vader, FastText).