An Experimental Study Of Netflix Use and the Effects of Autoplay on Watching Behaviors
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arXiv
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| Format: | Preprint |
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2024
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| author | Schaffner, Brennan Ulloa, Yaretzi Sahni, Riya Li, Jiatong Cohen, Ava Kim Messier, Natasha Gao, Lan Chetty, Marshini |
| author_facet | Schaffner, Brennan Ulloa, Yaretzi Sahni, Riya Li, Jiatong Cohen, Ava Kim Messier, Natasha Gao, Lan Chetty, Marshini |
| contents | Prior work on dark patterns, or manipulative online interfaces, suggests they have potentially detrimental effects on user autonomy. Dark pattern features, like those designed for attention capture, can potentially extend platform sessions beyond that users would have otherwise intended. Existing research, however, has not formally measured the quantitative effects of these features on user engagement in subscription video-on-demand platforms (SVODs). In this work, we conducted an experimental study with 76 Netflix users in the US to analyze the impact of a specific attention capture feature, autoplay, on key viewing metrics. We found that disabling autoplay on Netflix significantly reduced key content consumption aggregates, including average daily watching and average session length, partly filling the evidentiary gap regarding the empirical effects of dark pattern interfaces. We paired the experimental analysis with users' perceptions of autoplay and their viewing behaviors, finding that participants were split on whether the effects of autoplay outweigh its benefits, albeit without knowledge of the study findings. Our findings strengthen the broader argument that manipulative interface designs can and do affect users in potentially damaging ways, highlighting the continued need for considering user well-being and varied preferences in interface design. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_16040 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | An Experimental Study Of Netflix Use and the Effects of Autoplay on Watching Behaviors Schaffner, Brennan Ulloa, Yaretzi Sahni, Riya Li, Jiatong Cohen, Ava Kim Messier, Natasha Gao, Lan Chetty, Marshini Human-Computer Interaction Prior work on dark patterns, or manipulative online interfaces, suggests they have potentially detrimental effects on user autonomy. Dark pattern features, like those designed for attention capture, can potentially extend platform sessions beyond that users would have otherwise intended. Existing research, however, has not formally measured the quantitative effects of these features on user engagement in subscription video-on-demand platforms (SVODs). In this work, we conducted an experimental study with 76 Netflix users in the US to analyze the impact of a specific attention capture feature, autoplay, on key viewing metrics. We found that disabling autoplay on Netflix significantly reduced key content consumption aggregates, including average daily watching and average session length, partly filling the evidentiary gap regarding the empirical effects of dark pattern interfaces. We paired the experimental analysis with users' perceptions of autoplay and their viewing behaviors, finding that participants were split on whether the effects of autoplay outweigh its benefits, albeit without knowledge of the study findings. Our findings strengthen the broader argument that manipulative interface designs can and do affect users in potentially damaging ways, highlighting the continued need for considering user well-being and varied preferences in interface design. |
| title | An Experimental Study Of Netflix Use and the Effects of Autoplay on Watching Behaviors |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2412.16040 |