Cerca risorse accademiche

Richard Socher, Alex Perelygin, Jean Wu, Jason Chuang, Christopher D. Manning, Andrew Ng, Christopher Potts. Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing. 2013.

We consider the problem of classifying documents not by topic, but by overall sentiment, e.g., determining whether a review is positive or negative. Using movie reviews as data, we find that standard machine learning tec...

Materie / parole chiave: Natural language processing (Computer science); Sentiment analysis; Public opinion; Data processing; Electronic books

An important part of our information-gathering behavior has always been to find out what other people think. With the growing availability and popularity of opinion-rich resources such as online review sites and personal...

"This thesis examines whether unusually negative financial news is associated with increased short-term market volatility, measured by absolute VIX movements. The analysis is based on more than 1.3 million cleaned and de...

We report on a series of experiments with convolutional neural networks (CNN) trained on top of pre-trained word vectors for sentence-level classification tasks. We show that a simple CNN with little hyperparameter tunin...