Paper: SA-UZH: Verb-based Sentiment Analysis

ACL ID S14-2087
Title SA-UZH: Verb-based Sentiment Analysis
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2014
Authors

This paper describes the details of our system submitted to the SemEval-2014 shared task about aspect-based sentiment analysis on review texts. We participated in subtask 2 (prediction of the polarity of aspect terms) and 4 (prediction of the polarity of aspect categories). Our ap- proach to determine the sentiment of as- pect terms and categories is based on lin- guistic preprocessing, including a com- positional analysis and a verb resource, task-specific feature engineering and su- pervised machine learning techniques. We used a Logistic Regression classifier to make predictions, which were ranked above-average in the shared task.