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A three-stage quality evaluation method for experience products: taking animation as an example

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Abstract

The diversity and dynamics of quality index information bring challenges to quality assessment of experience products. This paper proposes a three-stage quality assessment method based on grounded theory, association analysis, combined weighting, sentiment analysis and cloud model. Firstly, based on online reviews, the true quality indicators of animation are recognized by grounded theory, and the relationships among quality indicators are identified by association analysis. Secondly, by introducing the principle of gaming, the combined weighting based on network opinion leader and network opinion follower is proposed. Finally, an animation comprehensive quality evaluation model based on cloud model and sentiment analysis is proposed. The feasibility and practicability of the method are verified on multiple animation datasets, and the quality levels of different sales products are obtained, providing a direction for animation quality improvement. Meanwhile, this paper further demonstrates the method's superiority by comparing it with other methods.

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The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China (No. 71672004).

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  1. Beijing Modern Manufacturing Development, School of Economics and Management, Beijing University of Technology, Beijing, 100124, China

    Qianqian Chen, Zhongjun Tang, Duokui He, Dongyuan Zhao & Jing Wang

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QC wrote the main manuscript text. ZT contributed the conceptualization and funding acquisition. DH performed the paper revisions. DZ contributed Supervision. JW performed the investigation. All authors reviewed and approved the final manuscript.

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Correspondence to Zhongjun Tang.

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Chen, Q., Tang, Z., He, D. et al. A three-stage quality evaluation method for experience products: taking animation as an example. Multimedia Systems 30, 203 (2024). https://doi.org/10.1007/s00530-024-01401-0

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