Just the Right Mood for HIT!

Qiu, Sihang; Gadiraju, Ujwal; Bozzon, Alessandro

doi:10.1007/978-3-030-50578-3_26

Cited by 5 publications

(6 citation statements)

References 29 publications

(28 reference statements)

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“…The subjective perception of crowd workers plays important roles in microtask crowdsourcing with regard to many aspects such as the quality and the incentive. Previous works have studied subjective perceptions concerning worker engagement [19,48,57], moods [58,68], satisfaction [51], and enjoyment [7,10].…”

Section: Subjective Perception In Crowdsourcingmentioning

confidence: 99%

“…Cheng et al proposed an effective way to measure worker efforts using "error-time area" (ETA), enabling a requester to rapidly evaluate the efficiency [9]. Recent studies have also shown that worker moods could affect quality-related crowdsourced outcomes [58,68]. Results revealed that workers in pleasant moods outperformed significantly over unpleasant workers.…”

Section: Subjective Perception In Crowdsourcingmentioning

confidence: 99%

“…Eyes, eyebrow, and mouth types are initialized according to workers' moods. Since previous studies have shown the importance of worker moods in crowdsourcing [58,68], we created a "mood" option by combining eyes, eyebrow, and mouth options. Note that in the original version of avataaars, the "mood" option does not exist -users need to customize moods by changing the emotion of eyes, eyebrow, and mouth.…”

Section: Avatar Designmentioning

confidence: 99%

“…There are four available gender options (non-binary, female, male, and others), seven available skin colors (tanned, yellow, pale, light, brown, dark brown, and black), and nine types of moods in three main categories (pleasant, unpleasant, and neutral). The instrument for measuring mood is called Pick-A-Mood [15], which is a robust and validated tool, and has been used in multiple HCI studies [58,68].…”

Section: Demographicmentioning

confidence: 99%

See 3 more Smart Citations

Using Worker Avatars to Improve Microtask Crowdsourcing

Qiu

Bozzon

Birk

et al. 2021

Proc. ACM Hum.-Comput. Interact.

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The future of crowd work has been identified to depend on worker satisfaction, but we lack a thorough understanding of how worker satisfaction can be increased in microtask crowdsourcing. Prior work has shown that one solution is to build tasks that are engaging. To facilitate engagement, two methods that have received attention in recent HCI literature are the use of video games and conversational interfaces. While these are largely different techniques, they aim for the same goal of reducing worker burden and increasing engagement in a task. On one hand, video games have huge motivation potential and translating game design elements for motivational purposes has shown positive effects. Recent work in games research has shown that the use of player avatars is effective in fostering interest, enjoyment, and other aspects pertaining to intrinsic motivation. On the other hand, conversational interfaces have been argued to have advantages over traditional GUIs due to facilitating a more human-like interaction. "Conversational" microtasking has recently been proposed to improve worker engagement in microtask marketplaces. The contexts of games and crowd work are underlined by the need to motivate and engage participants, yet the potential of using worker avatars to promote self-identification and improve worker satisfaction in microtask crowdsourcing has remained unexplored. Addressing this knowledge gap, we carried out a between-subject study involving 360 crowd workers. We investigated how worker avatars influence quality related outcomes of workers and their perceived experience, in conventional web and novel conversational interfaces. We equipped workers with the functionality of customizing their avatars, and selecting characterizations for their avatars, to understand whether identifying with an avatar can increase the motivation of workers. We found that using worker avatars with conversational interfaces can effectively reduce cognitive workload and increase worker retention. Our results indicate the occurrence of similarity and wishful avatar identification in crowdsourcing. Our findings have important implications in alleviating workers' perceived workload and on the design of crowdsourcing microtasks.CCS Concepts: • Information systems → Crowdsourcing; • Human-centered computing → Empirical studies in HCI.

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Section: Subjective Perception In Crowdsourcingmentioning

confidence: 99%

Section: Subjective Perception In Crowdsourcingmentioning

confidence: 99%

Section: Avatar Designmentioning

confidence: 99%

Section: Demographicmentioning

confidence: 99%

See 2 more Smart Citations

Using Worker Avatars to Improve Microtask Crowdsourcing

Qiu

Bozzon

Birk

et al. 2021

Proc. ACM Hum.-Comput. Interact.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Problemstellung. Crowdworker sind eventuell nicht in der richtigen Stimmung [21], um kreative Arbeit zu leisten, da sie eher monotone und repetitive Arbeitsaufträge gewohnt sind und zum Teil auch bevorzugen [18]. In die Rolle einer anderen Person zu schlüpfen könnte in diesem Fall zu kreativeren Arbeitsergebnissen führen [13,14,26].…”

Section: Steigerung Der Kreativität Des Crowdworkers (Iii)unclassified