Paper: UMCC_DLSI: A Probabilistic Automata for Aspect Based Sentiment Analysis

ACL ID S14-2129
Title UMCC_DLSI: A Probabilistic Automata for Aspect Based Sentiment Analysis
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2014
Authors

This work introduces a new approach for aspect based sentiment analysis task. Its main purpose is to automatically assign the correct polarity for the aspect term in a phrase. It is a probabilistic automata where each state consists of all the nouns, adjectives, verbs and adverbs found in an annotated corpora. Each one of them contains the number of occurrences in the annotated corpora for the four required polarities (i.e. positive, negative, neutral and conflict). Also, the transitions between states have been taken into account. These values were used to assign the predicted polarity when a pattern was found in a sentence; if a pattern cannot be applied, the probabilities of the polarities between states were computed in order to predict the right polarity. The system a...