A computational visual analysis of image design in social media car model communities

Jochen Wulf; Tobias Mettler; Stephan Ludwig; Dennis Herhausen

A computational visual analysis of image design in social media car model communities

Jochen Wulf, Tobias Mettler, Stephan Ludwig, Dennis Herhausen

Marketing

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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Abstract

While user-generated images represent important information sources in IS in general and in social media in particular, there is little research that analyzes image design and its effects on image popularity. We introduce an innovative computational approach to extract image design characteristics that includes convolutional neural network-based image classification, a dimensionality reduction via principal component analysis, manual measurement validation, and a regression analysis. An analysis of 790,775 car images from 17 brands posted in 68 car model communities on a social media platform reveals several effects of product presentation on image popularity that relate to the levels of utility reference, experience reference, and visual detail. A comparison of economy cars and premium cars shows that car class moderates these image design effects. Our results contribute to the extant literature on brand communities and content popularity in social media. The proposed computational visual analysis methodology may inform the study of other image-based IS.

Original language	English
Title of host publication	27th European Conference on Information Systems - Information Systems for a Sharing Society (ECIS 2019)
Subtitle of host publication	[Proceedings]
Editors	Jan vom Brocke, Shirley Gregor, Oliver Muller
Publisher	Association for Information Systems
Pages	1-16
Number of pages	16
ISBN (Electronic)	9781733632508
Publication status	Published - 2020
Event	27th European Conference on Information Systems: Information Systems for a Sharing Society, ECIS 2019 - Stockholm and Uppsala, Sweden Duration: 8 Jun 2019 → 14 Jun 2019

Publication series

Name	ECIS Proceedings
Volume	2019

Conference

Conference	27th European Conference on Information Systems: Information Systems for a Sharing Society, ECIS 2019
Country/Territory	Sweden
City	Stockholm and Uppsala
Period	8/06/19 → 14/06/19

Bibliographical note

Publisher Copyright:
© 27th European Conference on Information Systems - Information Systems for a Sharing Society, ECIS 2019. All rights reserved.

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

Keywords

Computational visual analysis
Convolutional neural networks
Image analysis
Product communities
Social media

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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Wulf et al_A computational visual analysis of image design in social media car model communitiesFinal published version, 7.28 MBLicence: Article 25fa Dutch Copyright Act

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Wulf, J., Mettler, T., Ludwig, S., & Herhausen, D. (2020). A computational visual analysis of image design in social media car model communities. In J. vom Brocke, S. Gregor, & O. Muller (Eds.), 27th European Conference on Information Systems - Information Systems for a Sharing Society (ECIS 2019): [Proceedings] (pp. 1-16). (ECIS Proceedings; Vol. 2019). Association for Information Systems. https://aisel.aisnet.org/ecis2019_rp/168/

Wulf, Jochen ; Mettler, Tobias ; Ludwig, Stephan et al. / A computational visual analysis of image design in social media car model communities. 27th European Conference on Information Systems - Information Systems for a Sharing Society (ECIS 2019): [Proceedings]. editor / Jan vom Brocke ; Shirley Gregor ; Oliver Muller. Association for Information Systems, 2020. pp. 1-16 (ECIS Proceedings).

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title = "A computational visual analysis of image design in social media car model communities",

abstract = "While user-generated images represent important information sources in IS in general and in social media in particular, there is little research that analyzes image design and its effects on image popularity. We introduce an innovative computational approach to extract image design characteristics that includes convolutional neural network-based image classification, a dimensionality reduction via principal component analysis, manual measurement validation, and a regression analysis. An analysis of 790,775 car images from 17 brands posted in 68 car model communities on a social media platform reveals several effects of product presentation on image popularity that relate to the levels of utility reference, experience reference, and visual detail. A comparison of economy cars and premium cars shows that car class moderates these image design effects. Our results contribute to the extant literature on brand communities and content popularity in social media. The proposed computational visual analysis methodology may inform the study of other image-based IS.",

keywords = "Computational visual analysis, Convolutional neural networks, Image analysis, Product communities, Social media",

author = "Jochen Wulf and Tobias Mettler and Stephan Ludwig and Dennis Herhausen",

note = "Publisher Copyright: {\textcopyright} 27th European Conference on Information Systems - Information Systems for a Sharing Society, ECIS 2019. All rights reserved. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 27th European Conference on Information Systems: Information Systems for a Sharing Society, ECIS 2019 ; Conference date: 08-06-2019 Through 14-06-2019",

year = "2020",

language = "English",

series = "ECIS Proceedings",

publisher = "Association for Information Systems",

pages = "1--16",

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Wulf, J, Mettler, T, Ludwig, S & Herhausen, D 2020, A computational visual analysis of image design in social media car model communities. in J vom Brocke, S Gregor & O Muller (eds), 27th European Conference on Information Systems - Information Systems for a Sharing Society (ECIS 2019): [Proceedings]. ECIS Proceedings, vol. 2019, Association for Information Systems, pp. 1-16, 27th European Conference on Information Systems: Information Systems for a Sharing Society, ECIS 2019, Stockholm and Uppsala, Sweden, 8/06/19. <https://aisel.aisnet.org/ecis2019_rp/168/>

A computational visual analysis of image design in social media car model communities. / Wulf, Jochen; Mettler, Tobias; Ludwig, Stephan et al.
27th European Conference on Information Systems - Information Systems for a Sharing Society (ECIS 2019): [Proceedings]. ed. / Jan vom Brocke; Shirley Gregor; Oliver Muller. Association for Information Systems, 2020. p. 1-16 (ECIS Proceedings; Vol. 2019).

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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AU - Mettler, Tobias

AU - Ludwig, Stephan

AU - Herhausen, Dennis

N1 - Publisher Copyright: © 27th European Conference on Information Systems - Information Systems for a Sharing Society, ECIS 2019. All rights reserved. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

PY - 2020

Y1 - 2020

N2 - While user-generated images represent important information sources in IS in general and in social media in particular, there is little research that analyzes image design and its effects on image popularity. We introduce an innovative computational approach to extract image design characteristics that includes convolutional neural network-based image classification, a dimensionality reduction via principal component analysis, manual measurement validation, and a regression analysis. An analysis of 790,775 car images from 17 brands posted in 68 car model communities on a social media platform reveals several effects of product presentation on image popularity that relate to the levels of utility reference, experience reference, and visual detail. A comparison of economy cars and premium cars shows that car class moderates these image design effects. Our results contribute to the extant literature on brand communities and content popularity in social media. The proposed computational visual analysis methodology may inform the study of other image-based IS.

AB - While user-generated images represent important information sources in IS in general and in social media in particular, there is little research that analyzes image design and its effects on image popularity. We introduce an innovative computational approach to extract image design characteristics that includes convolutional neural network-based image classification, a dimensionality reduction via principal component analysis, manual measurement validation, and a regression analysis. An analysis of 790,775 car images from 17 brands posted in 68 car model communities on a social media platform reveals several effects of product presentation on image popularity that relate to the levels of utility reference, experience reference, and visual detail. A comparison of economy cars and premium cars shows that car class moderates these image design effects. Our results contribute to the extant literature on brand communities and content popularity in social media. The proposed computational visual analysis methodology may inform the study of other image-based IS.

KW - Computational visual analysis

KW - Convolutional neural networks

KW - Image analysis

KW - Product communities

KW - Social media

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M3 - Conference contribution

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ER -

Wulf J, Mettler T, Ludwig S, Herhausen D. A computational visual analysis of image design in social media car model communities. In vom Brocke J, Gregor S, Muller O, editors, 27th European Conference on Information Systems - Information Systems for a Sharing Society (ECIS 2019): [Proceedings]. Association for Information Systems. 2020. p. 1-16. (ECIS Proceedings). Epub 2020 May 15.

A computational visual analysis of image design in social media car model communities

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

Access to Document

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