The Evaluation and Learning of Web Crawler Technology in the Field of Digital Media Art

Abstract

With the rapid advancement of digital technology, digital media art has progressively emerged as a novel darling in the contemporary art market, primarily due to its distinctive interactivity, generativity, and digital distribution methods.The appraisal of market value is crucial in the transaction of digital art, and web crawling technology presents an innovative approach for data acquisition and processing. This study is dedicated to exploring the convergence of digital media art and web crawling technology, conducting an in-depth investigation on the application of web crawlers in the determination of market value for digital art.In the context of developing a theoretical framework, a novel value assessment model is proposed by integrating the features of the digital art market with established value assessment theories. On this basis, a value assessment tool targeted at the digital media art market was developed.This tool integrates multiple factors such as historical transaction data of artworks, artist backgrounds, work style, and media exposure, and employs machine learning algorithms to conduct market value assessment of artworks.Case analyses have also confirmed the accuracy of the assessment results and the practicality of the assessment model.Results show that this assessment tool not only provides powerful market guidance for art investors and collectors but also offers a pricing decision basis for digital art trading platforms.This research not only provides new perspectives and practical tools for the assessment of digital art but also makes a valuable exploration into the application of web crawling technology in the acquisition of art data information.It is of positive significance for the value discovery of digital media art and the long-term healthy development of the art market.