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2019 | OriginalPaper | Buchkapitel

Toward’s Arabic Multi-modal Sentiment Analysis

verfasst von : Abdulrahman S. Alqarafi, Ahsan Adeel, Mandar Gogate, Kia Dashitpour, Amir Hussain, Tariq Durrani

Erschienen in: Communications, Signal Processing, and Systems

Verlag: Springer Singapore

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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.

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Literatur
1.
Zurück zum Zitat Morency, L.P., Mihalcea, R., Doshi, P.: Towards multimodal sentiment analysis: harvesting opinions from the web. In: Proceedings of the 13th International Conference on Multimodal Interfaces, pp. 169–176. ACM (2011) Morency, L.P., Mihalcea, R., Doshi, P.: Towards multimodal sentiment analysis: harvesting opinions from the web. In: Proceedings of the 13th International Conference on Multimodal Interfaces, pp. 169–176. ACM (2011)
2.
Zurück zum Zitat Wöllmer, M., Weninger, F., Knaup, T., Schuller, B., Sun, C., Sagae, K., Morency, L.P.: Youtube movie reviews: sentiment analysis in an audio-visual context. IEEE Intell. Syst. 28(3), 46–53 (2013) Wöllmer, M., Weninger, F., Knaup, T., Schuller, B., Sun, C., Sagae, K., Morency, L.P.: Youtube movie reviews: sentiment analysis in an audio-visual context. IEEE Intell. Syst. 28(3), 46–53 (2013)
3.
Zurück zum Zitat Poria, S., Cambria, E., Howard, N., Huang, G.B., Hussain, A.: Fusing audio, visual and textual clues for sentiment analysis from multimodal content. Neurocomputing 174, 50–59 (2016) Poria, S., Cambria, E., Howard, N., Huang, G.B., Hussain, A.: Fusing audio, visual and textual clues for sentiment analysis from multimodal content. Neurocomputing 174, 50–59 (2016)
4.
Zurück zum Zitat Poria, S., Cambria, E., Bajpai, R., Hussain, A.: A review of affective computing: from unimodal analysis to multimodal fusion. Inf. Fusion 37, 98–125 (2017) Poria, S., Cambria, E., Bajpai, R., Hussain, A.: A review of affective computing: from unimodal analysis to multimodal fusion. Inf. Fusion 37, 98–125 (2017)
5.
Zurück zum Zitat Rosas, V.P., Mihalcea, R., Morency, L.P.: Multimodal sentiment analysis of Spanish online videos. IEEE Intell. Syst. 28(3), 38–45 (2013) Rosas, V.P., Mihalcea, R., Morency, L.P.: Multimodal sentiment analysis of Spanish online videos. IEEE Intell. Syst. 28(3), 38–45 (2013)
6.
Zurück zum Zitat Zadeh, A., Zellers, R., Pincus, E., Morency, L.P.: MOSI: multimodal corpus of sentiment intensity and subjectivity analysis in online opinion videos. arXiv preprint arXiv:1606.06259 (2016) Zadeh, A., Zellers, R., Pincus, E., Morency, L.P.: MOSI: multimodal corpus of sentiment intensity and subjectivity analysis in online opinion videos. arXiv preprint arXiv:​1606.​06259 (2016)
7.
Zurück zum Zitat Wiebe, J., Wilson, T., Cardie, C.: Annotating expressions of opinions and emotions in language. Lang. Resourc. Eval. 39(2), 165–210 (2005) Wiebe, J., Wilson, T., Cardie, C.: Annotating expressions of opinions and emotions in language. Lang. Resourc. Eval. 39(2), 165–210 (2005)
Metadaten
Titel
Toward’s Arabic Multi-modal Sentiment Analysis
verfasst von
Abdulrahman S. Alqarafi
Ahsan Adeel
Mandar Gogate
Kia Dashitpour
Amir Hussain
Tariq Durrani
Copyright-Jahr
2019
Verlag
Springer Singapore
DOI
https://doi.org/10.1007/978-981-10-6571-2_290

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