Identifying Regional Trends in Avatar Customization
<p dir="ltr">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...
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2019
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| _version_ | 1864513515134386176 |
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| author | Peter Mawhorter (18602944) |
| author2 | Sercan Sengun (18602947) Haewoon Kwak (5747558) D. Fox Harrell (18602950) |
| author2_role | author author author |
| author_facet | Peter Mawhorter (18602944) Sercan Sengun (18602947) Haewoon Kwak (5747558) D. Fox Harrell (18602950) |
| author_role | author |
| dc.creator.none.fl_str_mv | Peter Mawhorter (18602944) Sercan Sengun (18602947) Haewoon Kwak (5747558) D. Fox Harrell (18602950) |
| dc.date.none.fl_str_mv | 2019-12-04T03:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1109/tg.2018.2835776 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Identifying_Regional_Trends_in_Avatar_Customization/25886920 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Information and computing sciences Human-centred computing Avatars Social network services Games Machine learning Training Market research Prototypes Artificial neural networks clustering algorithms cultural differences data analysis deep learning image processing unsupervised learning |
| dc.title.none.fl_str_mv | Identifying Regional Trends in Avatar Customization |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">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 U.S.-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.</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Transactions on Games<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/tg.2018.2835776" target="_blank">https://dx.doi.org/10.1109/tg.2018.2835776</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_57e9d24ecd781e43fc813ff58d4e437b |
| identifier_str_mv | 10.1109/tg.2018.2835776 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/25886920 |
| publishDate | 2019 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Identifying Regional Trends in Avatar CustomizationPeter Mawhorter (18602944)Sercan Sengun (18602947)Haewoon Kwak (5747558)D. Fox Harrell (18602950)Information and computing sciencesHuman-centred computingAvatarsSocial network servicesGamesMachine learningTrainingMarket researchPrototypesArtificial neural networksclustering algorithmscultural differencesdata analysisdeep learningimage processingunsupervised learning<p dir="ltr">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 U.S.-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.</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Transactions on Games<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/tg.2018.2835776" target="_blank">https://dx.doi.org/10.1109/tg.2018.2835776</a></p>2019-12-04T03:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1109/tg.2018.2835776https://figshare.com/articles/journal_contribution/Identifying_Regional_Trends_in_Avatar_Customization/25886920CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/258869202019-12-04T03:00:00Z |
| spellingShingle | Identifying Regional Trends in Avatar Customization Peter Mawhorter (18602944) Information and computing sciences Human-centred computing Avatars Social network services Games Machine learning Training Market research Prototypes Artificial neural networks clustering algorithms cultural differences data analysis deep learning image processing unsupervised learning |
| status_str | publishedVersion |
| title | 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_short | Identifying Regional Trends in Avatar Customization |
| title_sort | Identifying Regional Trends in Avatar Customization |
| topic | Information and computing sciences Human-centred computing Avatars Social network services Games Machine learning Training Market research Prototypes Artificial neural networks clustering algorithms cultural differences data analysis deep learning image processing unsupervised learning |