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      Quantifying the development of user-generated art during 2001–2010

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      PLoS ONE
      Public Library of Science

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          Abstract

          One of the main questions in the humanities is how cultures and artistic expressions change over time. While a number of researchers have used quantitative computational methods to study historical changes in literature, music, and cinema, our paper offers the first quantitative analysis of historical changes in visual art created by users of a social online network. We propose a number of computational methods for the analysis of temporal development of art images. We then apply these methods to a sample of 270,000 artworks created between 2001 and 2010 by users of the largest social network for art—DeviantArt ( www.deviantart.com). We investigate changes in subjects, techniques, sizes, proportions and also selected visual characteristics of images. Because these artworks are classified by their creators into two general categories—Traditional Art and Digital Art—we are also able to investigate if the use of digital tools has had a significant effect on the content and form of artworks. Our analysis reveals a number of gradual and systematic changes over a ten-year period in artworks belonging to both categories.

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          The openCV library

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            Image processing for artist identification

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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                2017
                8 August 2017
                : 12
                : 8
                : e0175350
                Affiliations
                [1 ] California Institute for Telecommunications and Information Technology’s Qualcomm Institute, University of California San Diego, San Diego, California, United States of America
                [2 ] Katana, San Diego, California, United States of America
                [3 ] Computer Science, The Graduate Center at the City University of New York, New York, United States of America
                Banner Alzheimer’s Institute, UNITED STATES
                Author notes

                Competing Interests: Jay Chow is employed by Katana. There are no patents, products in development or marketed products to declare. This does not alter our adherence to all the PLOS ONE policies on sharing data and materials, as detailed online in the guide for authors.

                • Conceptualization: MY JC LM.

                • Data curation: MY JC LM.

                • Formal analysis: MY.

                • Funding acquisition: LM.

                • Investigation: MY LM.

                • Methodology: MY LM.

                • Project administration: MY LM.

                • Resources: LM.

                • Software: MY JC.

                • Supervision: LM.

                • Validation: MY LM.

                • Visualization: MY JC LM.

                • Writing – original draft: MY LM.

                • Writing – review & editing: MY LM.

                Article
                PONE-D-16-22097
                10.1371/journal.pone.0175350
                5549703
                28792494
                21b154b5-1783-4609-bf2b-ec521d2ad464
                © 2017 Yazdani et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 1 June 2016
                : 25 March 2017
                Page count
                Figures: 10, Tables: 3, Pages: 24
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100000873, Andrew W. Mellon Foundation;
                Award ID: 20121945
                Award Recipient :
                This study was funded by Tools for the Analysis and Visualization of Large Image and Video Collections for the Humanities, Mellon Foundation, 4/2012-3/2015 ( https://mellon.org). Katana provided support in the form of salaries for authors [JC], but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.
                Categories
                Research Article
                Engineering and Technology
                Digital Imaging
                Research and Analysis Methods
                Imaging Techniques
                Computer and Information Sciences
                Network Analysis
                Social Networks
                Social Sciences
                Sociology
                Social Networks
                Social Sciences
                Archaeology
                Historical Archaeology
                Social Sciences
                Sociology
                Culture
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Multivariate Analysis
                Principal Component Analysis
                Physical Sciences
                Mathematics
                Statistics (Mathematics)
                Statistical Methods
                Multivariate Analysis
                Principal Component Analysis
                Research and Analysis Methods
                Imaging Techniques
                Photography
                Research and Analysis Methods
                Research Design
                Quantitative Analysis
                Custom metadata
                The data and code used in this study are all available in the GitHub repository: https://github.com/myazdani/DeviantArt-repo. The metadata for the images (URLs and dates uploaded) can be found here: https://github.com/myazdani/DeviantArt-repo/tree/master/_2014%20DeviantArt%20work/metadata I confirm that this information meets the standards required.

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                Uncategorized

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