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Quantifying the development of user-generated art during 2001-2010
Mehrdad Yazdani1, Jay Chow2, Lev Manovich3
1California Institute for Telecommunications and Information Technology's Qualcomm Institute, University of California San Diego, San Diego, California, United States of America.
Plos One
|August 10, 2017
Summary
This study quantitatively analyzes visual art trends on DeviantArt from 2001-2010. It reveals gradual, systematic changes in subjects, techniques, and visual characteristics across Traditional and Digital Art categories over time.
Area of Science:
- Digital Humanities
- Computational Social Science
- Art History
Background:
- Understanding cultural and artistic evolution is a key humanities question.
- Previous research used computational methods for literature, music, and cinema, but not visual art on social networks.
- DeviantArt, a large online art community, provides a unique dataset for studying visual art trends.
Purpose of the Study:
- To conduct the first quantitative analysis of historical changes in visual art from a social online network.
- To develop and apply computational methods for analyzing temporal art image development.
- To investigate changes in subjects, techniques, size, proportions, and visual characteristics of artworks.
Main Methods:
- Utilized a dataset of 270,000 artworks from DeviantArt (2001-2010).
- Developed novel computational methods for analyzing temporal art image evolution.
- Classified artworks into Traditional Art and Digital Art to assess the impact of digital tools.
Main Results:
- Identified gradual and systematic changes in visual art over a ten-year period.
- Observed shifts in subjects, techniques, and visual characteristics within both Traditional and Digital Art.
- The study provides insights into how digital tools may influence artistic content and form.
Conclusions:
- Computational analysis of large-scale online art datasets can reveal significant cultural and artistic trends.
- The study demonstrates the utility of quantitative methods in understanding the evolution of visual art.
- Findings contribute to the digital humanities by providing empirical evidence of art historical changes.
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