Conference Proceeding
Details
Citation
Alqarafi AS, Adeel A, Gogate M, Dashtipour K, Hussain A & Durrani T (2019) Towards Arabic multi-modal sentiment analysis. In: Liang Q, Mu J, Jia M, Wang W, Feng X & Zhang B (eds.) Communications, Signal Processing, and Systems. CSPS 2017. Lecture Notes in Electrical Engineering, 463. CSPS 2017: Communications, Signal Processing, and Systems, 14.07.2017-16.07.2017. Harbin, China: Springer, pp. 2378-2386. https://doi.org/10.1007/978-981-10-6571-2_290
Abstract
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.
Keywords
Arabic; Sentiment analysis; Multi-modal
Journal
Lecture Notes in Electrical Engineering
Status | Published |
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Funders | Engineering and Physical Sciences Research Council |
Title of series | Lecture Notes in Electrical Engineering |
Number in series | 463 |
Publication date | 31/12/2019 |
Publication date online | 07/06/2018 |
URL | http://hdl.handle.net/1893/27750 |
Publisher | Springer |
Place of publication | Harbin, China |
ISSN of series | 1876-1100 |
ISBN | 978-981-10-6570-5; 978-981-10-6571-2 |
Conference | CSPS 2017: Communications, Signal Processing, and Systems |
Dates | – |
People (2)
Assoc. Prof. in Artificial Intelligence, Computing Science and Mathematics - Division
Honorary Professor, Computing Science