Target-dependent Sentiment Analysis of Tweets using a Bi-directional Gated Recurrent Unit

Mohammed Jabreel, Antonio Moreno

Abstract

Targeted sentiment analysis classifies the sentiment polarity towards a certain target in a given text. In this paper, we propose a target-dependent bidirectional gated recurrent unit (TD-biGRU) for target-dependent sentiment analysis of tweets. The proposed model has the ability to represent the interaction between the targets and their contexts. We have evaluated the effectiveness of the proposed model on a benchmark dataset from Twitter. The experiments show that our proposed model outperforms the state-of-the-are methods for target-dependent sentiment analysis.

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Paper Citation


in Harvard Style

Jabreel M. and Moreno A. (2017). Target-dependent Sentiment Analysis of Tweets using a Bi-directional Gated Recurrent Unit . In Proceedings of the 13th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST, ISBN 978-989-758-246-2, pages 80-87. DOI: 10.5220/0006299900800087


in Bibtex Style

@conference{webist17,
author={Mohammed Jabreel and Antonio Moreno},
title={Target-dependent Sentiment Analysis of Tweets using a Bi-directional Gated Recurrent Unit},
booktitle={Proceedings of the 13th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,},
year={2017},
pages={80-87},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006299900800087},
isbn={978-989-758-246-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 13th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,
TI - Target-dependent Sentiment Analysis of Tweets using a Bi-directional Gated Recurrent Unit
SN - 978-989-758-246-2
AU - Jabreel M.
AU - Moreno A.
PY - 2017
SP - 80
EP - 87
DO - 10.5220/0006299900800087