Identifying regional trends in avatar customization

Since virtual identities such as social media profiles and avatars have become a common venue for self-expression, it has become important to consider the ways in which existing systems embed the values of their designers. In order to design virtual identity systems that reflect the needs and prefer...

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Main Authors: MAWHORTER, Peter, SENGUN, Sercan, KWAK, Haewoon, HARRELL, D. FOX
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Language:English
Published: Institutional Knowledge at Singapore Management University 2019
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Online Access:https://ink.library.smu.edu.sg/sis_research/5328
https://ink.library.smu.edu.sg/context/sis_research/article/6332/viewcontent/identifying___PV.pdf
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Institution: Singapore Management University
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spelling sg-smu-ink.sis_research-63322020-10-23T07:41:11Z Identifying regional trends in avatar customization MAWHORTER, Peter SENGUN, Sercan KWAK, Haewoon HARRELL, D. FOX Since virtual identities such as social media profiles and avatars have become a common venue for self-expression, it has become important to consider the ways in which existing systems embed the values of their designers. In order to design virtual identity systems that reflect the needs and preferences of diverse users, understanding how the virtual identity construction differs between groups is important. This paper presents a new methodology that leverages deep learning and differential clustering for comparative analysis of profile images, with a case study of almost 100 000 avatars from a large online community using a popular avatar creation platform. We use novelty discovery to segment the avatars, then cluster avatars by region to identify visual trends among low- and high-novelty avatars. We find that avatar customization correlates with increased social activity, and we are able to identify distinct visual trends among the US.-region and Japan-region profiles. Among these trends, realistic, idealistic, and creative self-representation can be distinguished. We observe that the realistic self-expression mirrors regional demographics, idealistic self-expression reflects shared mass-media tropes, and creative self-expression propagates within the communities. 2019-12-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/5328 info:doi/10.1109/TG.2018.2835776 https://ink.library.smu.edu.sg/context/sis_research/article/6332/viewcontent/identifying___PV.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Artificial neural networks avatars clustering algorithms cultural differences data analysis deep learning image processing unsupervised learning Databases and Information Systems Digital Communications and Networking Theory and Algorithms
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Artificial neural networks
avatars
clustering algorithms
cultural differences
data analysis
deep learning
image processing
unsupervised learning
Databases and Information Systems
Digital Communications and Networking
Theory and Algorithms
spellingShingle Artificial neural networks
avatars
clustering algorithms
cultural differences
data analysis
deep learning
image processing
unsupervised learning
Databases and Information Systems
Digital Communications and Networking
Theory and Algorithms
MAWHORTER, Peter
SENGUN, Sercan
KWAK, Haewoon
HARRELL, D. FOX
Identifying regional trends in avatar customization
description Since virtual identities such as social media profiles and avatars have become a common venue for self-expression, it has become important to consider the ways in which existing systems embed the values of their designers. In order to design virtual identity systems that reflect the needs and preferences of diverse users, understanding how the virtual identity construction differs between groups is important. This paper presents a new methodology that leverages deep learning and differential clustering for comparative analysis of profile images, with a case study of almost 100 000 avatars from a large online community using a popular avatar creation platform. We use novelty discovery to segment the avatars, then cluster avatars by region to identify visual trends among low- and high-novelty avatars. We find that avatar customization correlates with increased social activity, and we are able to identify distinct visual trends among the US.-region and Japan-region profiles. Among these trends, realistic, idealistic, and creative self-representation can be distinguished. We observe that the realistic self-expression mirrors regional demographics, idealistic self-expression reflects shared mass-media tropes, and creative self-expression propagates within the communities.
format text
author MAWHORTER, Peter
SENGUN, Sercan
KWAK, Haewoon
HARRELL, D. FOX
author_facet MAWHORTER, Peter
SENGUN, Sercan
KWAK, Haewoon
HARRELL, D. FOX
author_sort MAWHORTER, Peter
title Identifying regional trends in avatar customization
title_short Identifying regional trends in avatar customization
title_full Identifying regional trends in avatar customization
title_fullStr Identifying regional trends in avatar customization
title_full_unstemmed Identifying regional trends in avatar customization
title_sort identifying regional trends in avatar customization
publisher Institutional Knowledge at Singapore Management University
publishDate 2019
url https://ink.library.smu.edu.sg/sis_research/5328
https://ink.library.smu.edu.sg/context/sis_research/article/6332/viewcontent/identifying___PV.pdf
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