In text analysis you can broadly focus either on style or on topic. Stylometry does the former and typically focuses on highly frequent function words; this tec

In text analysis you can broadly focus either on style or on topic. Stylometry does the former and typically focuses on highly frequent function words; this technique is good at identifying authors. There are various techniques that focus on topics such as distributional semantic models and bag-of-word models; these techniques are good at clustering documents about the same topics together (regardless of author style). I think that in both cases a text can be reduced by the model to a single vector, which could be considered a hash, but in the end what matters is how well the models perform on a task such as identifying authors or finding documents on a given topic.