Splitting by whole words makes "unhappiness" a single token. If the model never saw that word in training, it becomes unknown and its meaning is lost.
Word tokenization treats “unhappiness” as one indivisible unit. If it was not in the training vocabulary, all of its meaning is simply lost — even though “happy” certainly was there.
