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YouTube Video Ranking by Aspect-Based Sentiment Analysis on User Feedback

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Soft Computing and Signal Processing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 900))

Abstract

In the current big data and Internet of things world, a huge amount of data is available in the form of multimedia, shared on Web 2.0 platforms. Today, in the online smart learning process, the most widely used online video repository is YouTube, which also provides a place for users to express their views about videos in the form comments and rating. These user comments are still unexplored in the context of ranking in retrieval. Majorly, rating based on like/dislike is the only criterion considered to decide the relevancy and quality and in determining the ranking of the videos. Sometimes, the relevancy of the video is unveiled after watching the video, and as a result of this, irrelevant videos may be ranked higher. In this paper, we have investigated the impact of different aspects of the video’s subject from the user comments in the video retrieval using aspect-based sentiment analysis.

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Acknowledgements

We would like to extend our acknowledgement to all the volunteers for carrying out sentiment analysis on a huge database in order to achieve survey-based experimental results.

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Authors and Affiliations

  1. Malaviya National Institute of Technology, Jaipur, India

    Ganpat Singh Chauhan & Yogesh Kumar Meena

Authors
  1. Ganpat Singh Chauhan
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  2. Yogesh Kumar Meena
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Corresponding author

Correspondence to Ganpat Singh Chauhan .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Software Engineering, Monmouth University, West Long Branch, NJ, USA

    Jiacun Wang

  2. Department of Information Technology, National Institute of Technology Karnataka, Surathkal, Mangaluru, Karnataka, India

    G. Ram Mohana Reddy

  3. Department of Computer Science and Engineering, JNTUH College of Engineering Hyderabad, Hyderabad, Telangana, India

    V. Kamakshi Prasad

  4. Department of Electronics and Communication Engineering, Malla Reddy College of Engineering and Technology, Secunderabad, Telangana, India

    V. Sivakumar Reddy

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Cite this paper

Chauhan, G.S., Meena, Y.K. (2019). YouTube Video Ranking by Aspect-Based Sentiment Analysis on User Feedback. In: Wang, J., Reddy, G., Prasad, V., Reddy, V. (eds) Soft Computing and Signal Processing . Advances in Intelligent Systems and Computing, vol 900. Springer, Singapore. https://doi.org/10.1007/978-981-13-3600-3_6

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