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Opinion Extraction and Classification of Real-Time YouTube Cooking Recipes Comments

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Abstract

Applications based on Opinion Mining and Sentiment Analysis are critical tools for information-gathering to find out what people are thinking. It is one of the most active research areas in Natural Language Processing. In this paper, we develop a real-time system to extract and classify the YouTube cooking recipes reviews automatically. This system is based on Support vector machine approach and deals with the social media text characteristics. The proposed system collects data in real time from YouTube according to a user request. After it filters opinion texts from the other content, then it classifies it in (positive/negative) opinion. To improve the performance of our system we proposed some algorithms that constructed on sentiment bags, based on emoticons and injections.

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Correspondence to Randa Benkhelifa .

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Benkhelifa, R., Laallam, F.Z. (2018). Opinion Extraction and Classification of Real-Time YouTube Cooking Recipes Comments. In: Hassanien, A., Tolba, M., Elhoseny, M., Mostafa, M. (eds) The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2018). AMLTA 2018. Advances in Intelligent Systems and Computing, vol 723. Springer, Cham. https://doi.org/10.1007/978-3-319-74690-6_39

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  • DOI: https://doi.org/10.1007/978-3-319-74690-6_39

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-74689-0

  • Online ISBN: 978-3-319-74690-6

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