Research Output

Toward's Arabic multi-modal sentiment analysis

  In everyday life, people use internet to express and share opinions, facts, and sentiments about products and services. In addition, social media applications such as Facebook, Twitter, WhatsApp, Snapchat etc., have become important information sharing platforms. Apart from these, a collection of product reviews, facts, poll information, etc., is a need for every company or organization ranging from start-ups to big firms and governments. Clearly, it is very challenging to analyse such big data to improve products, services, and satisfy customer requirements. Therefore, it is necessary to automate the evaluation process using advanced sentiment analysis techniques. Most of previous works focused on uni-modal sentiment analysis mainly textual model. In this paper, a novel Arabic multimodal dataset is presented and validated using state-of-the-art support vector machine (SVM) based classification method.

  • Date:

    07 June 2018

  • Publication Status:

    Published

  • Publisher

    Springer

  • DOI:

    10.1007/978-981-10-6571-2_290

  • Funders:

    Engineering and Physical Sciences Research Council

Citation

Alqarafi, A., Adeel, A., Gogate, M., Dashitpour, K., Hussain, A., & Durrani, T. (2019). Toward's Arabic multi-modal sentiment analysis. https://doi.org/10.1007/978-981-10-6571-2_290

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