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Department of Electrical Engineering and Computer Science
Smart Input Device Laboratory
2. Conference Papers
Exploring Intervention Techniques to Alleviate Negative Emotions during Video Content Moderation Tasks as a Worker-centered Task Design
Lee, Dokyun
;
Seo, Sangeun
;
Park, Chanwoo
;
Kim, Sunjun
;
Chang, Buru
;
Song, Jean Y.
Department of Electrical Engineering and Computer Science
Smart Input Device Laboratory
2. Conference Papers
Department of Electrical Engineering and Computer Science
DGIST Intelligence Augmentation Group
2. Conference Papers
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Title
Exploring Intervention Techniques to Alleviate Negative Emotions during Video Content Moderation Tasks as a Worker-centered Task Design
Issued Date
2024-07-01
Citation
Lee, Dokyun. (2024-07-01). Exploring Intervention Techniques to Alleviate Negative Emotions during Video Content Moderation Tasks as a Worker-centered Task Design. 2024 ACM Designing Interactive Systems Conference, DIS 2024, 1701–1721. doi: 10.1145/3643834.3660708
Type
Conference Paper
ISBN
9798400705830
Abstract
Videos are dynamic and multi-modal compared to other types of content, making automatic fltering difcult, which is why content moderators play a crucial role. However, video content moderators are exposed to more profound emotional labor because videos contain rich visual information, sometimes including even harmful content, such as violent or terrifying scenes. In this work, we explore the efect of six intervention techniques on alleviating negative emotions during video content moderation tasks. We conducted one online crowdsourcing experiment and two controlled user studies to fnd out that (i) interleaving with positive videos or (ii) cartoonization could signifcantly reduce negative emotions in the moderators. Participants reported that the advantages of these approaches are in helping reduce negative emotions at the time of moderation while existing approaches focus on post-task activities (e.g., relaxation, talking with others, or getting a hobby). We discuss the applicability of our fndings to broader tasks, including improvement in intervention techniques. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.
URI
http://hdl.handle.net/20.500.11750/57866
DOI
10.1145/3643834.3660708
Publisher
Association for Computing Machinery, Inc
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