Nice work for you! However, it seems like the sentiment analysis is reeeeally subjective. Why is 'mother' sometimes negative and sometimes positive? Why is 'sir' positive? Why is 'funny' negative? Why is 'fast' positive? Is it positive if you 'drive too fast'? Is 'dark' negative in 'dark-haired beauty'? Is 'eat' positive if you "have nothing to eat"? Well, perhaps we can count more on 'nothing'. But then, is 'nothing' negative if you have "nothing to fear"? This last phrase is comprised of two supposed negatives but in overall it has a positive sentiment.

Perhaps there is something I don't understand well with how this works but it seems very simplistic and misleading to take words out of context like that. Is sentiment analysis a thing? I guess it could be improved if it worked more like automated translators do, working with large volumes of data and learning to more or less associate words depending on their context, but it still seems weird to me to decide on "sentiment". This is the first time I'm seeing this so please let me know if I'm wrong.