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<p>In the era of media convergence, the communication effectiveness of short video news in the ecological environment directly affects the development and innovation of short video news, and it can only survive by constantly adapting. In this paper, we first analyze the effectiveness of short video news from four dimensions based on the AISAS theoretical model of the four degrees of communication effectiveness evaluation method. Secondly, we select the clustering analysis method in data mining technology, establish the K-Means model, group the data, randomly select the cluster centers, and then calculate the distance between each object and each sub-cluster center. Then the optimization of the K-Means algorithm is proposed for the problem of slow convergence of the algorithm. Finally, the number of iterations and the accuracy of the optimized K-Means algorithm are analyzed and compared. The data of this study show that the average iteration time of the optimized K-Means algorithm is shortened by 9 seconds, and the accuracy rate is increased by 4% and approaches 100% many times. The efficiency of the optimized K-Means model has been significantly improved, and the accuracy rate can be maintained at a high level.</p>
</abstract>

In the era of media convergence, the communication effectiveness of short video news in the ecological environment directly affects the development and innovation of short video news, and it can only survive by constantly adapting. In this paper, we first analyze the effectiveness of short video news from four dimensions based on the AISAS theoretical model of the four degrees of communication effectiveness evaluation method. Secondly, we select the clustering analysis method in data mining technology, establish the K-Means model, group the data, randomly select the cluster centers, and then calculate the distance between each object and each sub-cluster center. Then the optimization of the K-Means algorithm is proposed for the problem of slow convergence of the algorithm. Finally, the number of iterations and the accuracy of the optimized K-Means algorithm are analyzed and compared. The data of this study show that the average iteration time of the optimized K-Means algorithm is shortened by 9 seconds, and the accuracy rate is increased by 4% and approaches 100% many times. The efficiency of the optimized K-Means model has been significantly improved, and the accuracy rate can be maintained at a high level.

Analysis of the effectiveness of short video news dissemination based on data mining technology

Chongqing Open University (Chongqing Technology and Business Institute)

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

In the era of media convergence, the communication effectiveness of short video news in the ecological environment directly affects the development and...

Analysis of the effectiveness of short video news dissemination based on data mining technology

Publié en ligne: 04 oct. 2023

Pages: -

Reçu: 21 oct. 2022

Accepté: 14 avr. 2023

DOI: https://doi.org/10.2478/amns.2023.2.00499

Mots clés
Propagation effectiveness, AISAS evaluation model, Data mining techniques, K-Means algorithm, Cluster analysis

© 2023 Yi Tan, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Analysis of the effectiveness of short video news dissemination based on data mining technology

Publié en ligne: 04 oct. 2023

Pages: -

Reçu: 21 oct. 2022

Accepté: 14 avr. 2023

DOI: https://doi.org/10.2478/amns.2023.2.00499

Mots clésPropagation effectiveness, AISAS evaluation model, Data mining techniques, K-Means algorithm, Cluster analysis

© 2023 Yi Tan, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mots clés
Propagation effectiveness, AISAS evaluation model, Data mining techniques, K-Means algorithm, Cluster analysis