Algorithm Embedding and Optimization of Rural Image Propagation in the View of Artificial Intelligence Generation Content_Vol. 2 No. 2 (JBDC 2024)_Journal of Big Data and Computing (ISSN: 2959-0590)

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Algorithm Embedding and Optimization of Rural Image Propagation in the View of Artificial Intelligence Generation Content

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DOI: https://doi.org/10.62517/jbdc.202401213

Author(s)

Jingjing Cao*

Affiliation(s)

School of Culture and Media, Xi’an Eurasia University, Xi’an, Shaanxi, China *Corresponding Author.

Abstract

The application of AIGC technology on various media platforms has brought numerous research hotspots to the media field. In this article, the author analyzes the current situation of rural image dissemination and the opportunities and problems that AIGC brings to it. The author believes that the changes brought by AIGC and algorithms are mainly reflected in three aspects: reshaping content and value through data-driven and AI generated content; achieve channels and participation guidance by using algorithms to enhance user engagement; promote precise push and feedback by utilize AIGC and algorithms to achieve precise propagation. However, there are also problems such as the singularity of "rural image production", the niche of "communication circles", and the fade of creative enthusiasm and creativity. Therefore, based on AIGC and algorithm technology, the author believes that analysis can be conducted from three dimensions: algorithm content recommendation, algorithm sentiment embedding, and algorithm interaction optimization. Suggestions are proposed from three aspects, the first one is establishing a three-dimensional rural image through algorithm content recommendation, the second one is building a humanistic communication system through algorithmic emotional embedding, and the last one is achieving two-way interaction between rural and urban residents through algorithmic interactive optimization.

Keywords

AIGC; Algorithm; Rural Image; Algorithm Embedding; Algorithm Optimization

References

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