@inproceedings{76a17ce1fe7b4217bebeb4fe8ed440c7,
title = "INSIGHT Galway: Syntactic and Lexical Features for Aspect Based Sentiment Analysis",
abstract = "This work analyses various syntactic and lexical features for sentence level aspect based sentiment analysis. The task focuses on detection of a writer{\textquoteright}s sentiment towards an aspect which is explicitly mentioned in a sentence. The target sentiment polarities are positive, negative, conflict and neutral. We use a supervised learning approach, evaluate various features and report accuracies which are much higher than the provided baselines. Best features include unigrams, clauses, dependency relations and SentiWordNet polarity scores.",
author = "Sapna Negi and Paul Buitelaar",
note = "Publisher Copyright: {\textcopyright} 8th International Workshop on Semantic Evaluation, SemEval 2014 - co-located with the 25th International Conference on Computational Linguistics, COLING 2014, Proceedings. All rights reserved.; 8th International Workshop on Semantic Evaluation, SemEval 2014 ; Conference date: 23-08-2014 Through 24-08-2014",
year = "2014",
doi = "10.3115/v1/s14-2058",
language = "English",
series = "8th International Workshop on Semantic Evaluation, SemEval 2014 - co-located with the 25th International Conference on Computational Linguistics, COLING 2014, Proceedings",
publisher = "Association for Computational Linguistics (ACL)",
pages = "346--350",
editor = "Preslav Nakov and Torsten Zesch",
booktitle = "8th International Workshop on Semantic Evaluation, SemEval 2014 - co-located with the 25th International Conference on Computational Linguistics, COLING 2014, Proceedings",
}