research-article

Video clip recommendation model by sentiment analysis of time-sync comments

Authors:

Zhiwei ZhangAuthors Info & Claims

Multimedia Tools and Applications, Volume 79, Issue 45-46

Pages 33449 - 33466

https://doi.org/10.1007/s11042-019-7578-4

Published: 01 December 2020 Publication History

Abstract

With the advent of video time-sync comments, users can not only comment the videos on the Internet, but also share their feelings with others. However, the number of the videos on the Internet is so huge that users do not have enough time and energy to watch all the videos. How to recommend the videos suitable for users has become an important problem. The traditional video sentiment analysis methods can not work effectively and the results are not easy to explain. In this paper, an emotion recognition algorithm based on sync-time comments is proposed, as a basis for the recommendation of video clips. First, we propose a formal description of video clips recommendation based on sentiment analysis. Secondly, by constructing the classification of time-sync comments based on Latent Dirichlet Allocation (LDA) topic model, we evaluate the emotion vector of the words in time-sync comments. Meanwhile, the video clips are recommended according to the emotion relationships among the video clips. The experimental results show that the proposed model is effective in analyzing the complex sentiment of different kinds of text information.

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Cited By

Wang HMaslim MHong W(2024)Personalized time-sync comment generation based on a multimodal transformerMultimedia Systems10.1007/s00530-024-01301-330:2Online publication date: 30-Mar-2024
https://dl.acm.org/doi/10.1007/s00530-024-01301-3
Al-Qablan TMohd Noor MAl-Betar MKhader A(2023)A survey on sentiment analysis and its applicationsNeural Computing and Applications10.1007/s00521-023-08941-y35:29(21567-21601)Online publication date: 1-Oct-2023
https://dl.acm.org/doi/10.1007/s00521-023-08941-y

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Information & Contributors

Information

Published In

cover image Multimedia Tools and Applications

Multimedia Tools and Applications Volume 79, Issue 45-46

Dec 2020

1330 pages

ISSN:1380-7501

Issue’s Table of Contents

© Springer Science+Business Media, LLC, part of Springer Nature 2019.

Publisher

Kluwer Academic Publishers

United States

Publication History

Published: 01 December 2020

Accepted: 03 April 2019

Revision received: 03 March 2019

Received: 18 June 2018

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Suzhou University
The city of Suzhou
Anhui Educational Department
National Natural Science Foundation of China

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Citations

Cited By

Wang HMaslim MHong W(2024)Personalized time-sync comment generation based on a multimodal transformerMultimedia Systems10.1007/s00530-024-01301-330:2Online publication date: 30-Mar-2024
https://dl.acm.org/doi/10.1007/s00530-024-01301-3
Al-Qablan TMohd Noor MAl-Betar MKhader A(2023)A survey on sentiment analysis and its applicationsNeural Computing and Applications10.1007/s00521-023-08941-y35:29(21567-21601)Online publication date: 1-Oct-2023
https://dl.acm.org/doi/10.1007/s00521-023-08941-y

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