Natural Language Processing and Sentiment Analysis
The communication protocol between humans is natural language. Humans communicate with each other and express their private states using language in the form of text or speech. Furthermore, language may be considered as the projection of human knowledge and intelligence. Hence, natural language is the right source of data to understand humans, to represent their intelligence and to communicate with them. However, natural language is unstructured data and it cannot be directly used by a computer system.
In this tutorial, we will describe how to represent natural language in order to be processed by a computer, or in other words, how to build features that represent natural language. We will introduce Deep Learning methods for the extraction of rich linguistic features from written utterances, not limited to superficial views of the text as a bag or sequence of words, but including the syntactic (structural) analysis of the text. Moreover, we will show the usefulness of these linguistic features for the development of opinion classification systems, which is crucial for Sentiment Analysis tasks. Likewise, we will focus on the development of polarity classification methods grounded in Deep Learning.