Social Media and Digital Collaboration
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Paper Number
2524
Paper Type
short
Description
The COVID-19 pandemic accelerated the implementation and adoption of new features in web-conferencing systems (WCSs), such as custom backgrounds (CBs) that mask the real physical background with a custom, i.e., user chosen, background. In this work, we explore what types of backgrounds are selected and why they are used by analyzing text and images from Twitter. We find that different types of CBs allow users to satisfy psychological needs in virtual collaboration and identify emerging practices regarding the selection of backgrounds, in general, and with respect to gender differences. Our analysis reveals that CBs showing real objects get commonly replaced or augmented by artificial, non-photorealistic content such as cartoon style memes, scenes of computer games or company logos. By leveraging novel image analysis techniques, we also contribute methodologically to social media analytics.
Recommended Citation
Schneider, Johannes; Hacker, Janine; Litvinova, Yulia; Handali, Joshua Peter; and vom Brocke, Jan, "Exploring the Use of Backgrounds in Web-conferencing with Image and Text Analysis" (2021). ICIS 2021 Proceedings. 14.
https://aisel.aisnet.org/icis2021/social_media/social_media/14
Exploring the Use of Backgrounds in Web-conferencing with Image and Text Analysis
The COVID-19 pandemic accelerated the implementation and adoption of new features in web-conferencing systems (WCSs), such as custom backgrounds (CBs) that mask the real physical background with a custom, i.e., user chosen, background. In this work, we explore what types of backgrounds are selected and why they are used by analyzing text and images from Twitter. We find that different types of CBs allow users to satisfy psychological needs in virtual collaboration and identify emerging practices regarding the selection of backgrounds, in general, and with respect to gender differences. Our analysis reveals that CBs showing real objects get commonly replaced or augmented by artificial, non-photorealistic content such as cartoon style memes, scenes of computer games or company logos. By leveraging novel image analysis techniques, we also contribute methodologically to social media analytics.
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16-SocMedia