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Target-Dependent Sentiment Analysis of Tweets Using Bidirectional Gated Recurrent Neural Networks

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Advances in Hybridization of Intelligent Methods

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 85))

Abstract

The task of target-dependent sentiment analysis aims to identify the sentiment polarity towards a certain target in a given text. All the existing models of this task assume that the target is known. This fact has motivated us to develop an end-to-end target-dependent sentiment analysis system. To the extent of our knowledge, this is the first system that identifies and extract the target of the tweets. The proposed system is composed of two main steps. First, the targets of the tweet to be analysed are extracted. Afterwards, the system identifies the polarities of the tweet towards each extracted target. We have evaluated the effectiveness of the proposed model on a benchmark dataset from Twitter. The experiments show that our proposed system outperforms the state-of-the-are methods for target-dependent sentiment analysis.

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Acknowledgements

The authors acknowledge the support of Univ. Rovira i Virgili through a Martí i Franqués Ph.D. grant, the assistant/teaching grant for the Department of Computer Engineering and Mathematics and the Research Support Funds 2016PFR-URV-B2-60.

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Authors and Affiliations

  1. Intelligent Technologies for Advanced Knowledge Acquisition (ITAKA), Departament d’Enginyeria Informàtica i Matemàtiques, Universitat Rovira i Virgili, Av. Països Catalans, 26, 43007, Tarragona, Spain

    Mohammed Jabreel, Fadi Hassan & Antonio Moreno

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  1. Mohammed Jabreel
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  2. Fadi Hassan
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  3. Antonio Moreno
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Correspondence to Mohammed Jabreel .

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Editors and Affiliations

  1. School of Engineering, Department of Computer Engineering and Informatics, University of Patras, Patras, Greece

    Ioannis Hatzilygeroudis

  2. The Faculty of Engineering, Environment and Computing, School of Computing, Coventry University, Coventry, United Kingdom

    Vasile Palade

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Jabreel, M., Hassan, F., Moreno, A. (2018). Target-Dependent Sentiment Analysis of Tweets Using Bidirectional Gated Recurrent Neural Networks. In: Hatzilygeroudis, I., Palade, V. (eds) Advances in Hybridization of Intelligent Methods. Smart Innovation, Systems and Technologies, vol 85. Springer, Cham. https://doi.org/10.1007/978-3-319-66790-4_3

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  • DOI: https://doi.org/10.1007/978-3-319-66790-4_3

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  • Online ISBN: 978-3-319-66790-4

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