Discourse structure is the hidden link between surface features and document-level
properties, such as sentiment polarity. We show that the discourse analyses produced by …

Opinion mining (also called sentiment analysis) is a type of natural language processing for
computing people's opinions and emotions. It detects opinions from structured, semi …

Prominent applications of sentiment analysis are countless, covering areas such as
marketing, customer service and communication. The conventional bag-of-words approach …

While GPT-2 generates sentences that are remarkably human-like, longer documents can
ramble and do not follow human-like writing structure. We study the problem of imposing …

Using rhetorical structure in sentiment analysis Page 1 JULY 2015 | VOL. 58 | NO. 7 |
COMMUNICATIONS OF THE ACM 69 DOI:10.1145/2699418 A deep, fine-grain analysis of …

As labeling schemas evolve over time, small differences can render datasets following older
schemas unusable. This prevents researchers from building on top of previous annotation …

Computational approaches to opinion mining have mostly focused on polarity detection of
product reviews by classifying the given text as positive, negative or neutral. While, there is …

This monograph proposes a comprehensive and fully automatic approach to designing text
analysis pipelines for arbitrary information needs that are optimal in terms of run-time …

Using deep learning models to solve sentiment analysis of sentences is still a challenging
task. Long short-term memory (LSTM) network solves the gradient disappeared problem …

In computational linguistics, sentiment analysis refers to the classification of opinions in a
positive class or a negative class. There exist a lot of different methods for sentiment …