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Mining User Experience Dimensions from Mental Illness Apps

机译:从精神疾病应用程序的挖掘用户体验尺寸

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Mental illness is prevalent, the primary cause of disability worldwide, and regardless of the extensive treatment choices. Mobile apps provide greater support for depression treatment that eliminates the communication barriers. This perspective can be dropped with poor application design. Our goal is to mining the user experience (UX) dimensions from top-n mental illness apps reviews that will help to design the better application for persons with severe mental illness (SMI) and cognitive deficits. In this paper, we extracted the key UX dimension from a huge corpus of mental illness apps reviews using unsupervised Latent Dirichlet Analysis (LDA). Finally, LDA uncovered 20 UX dimensions that need to consider for mental illness app design in order to promote the positive UX by reducing the cognitive load of app end users.
机译:精神疾病普遍,普遍的伤残原因,无论广泛的治疗选择如何。移动应用程序对消除通信障碍的抑郁处理提供了更大的支持。这种观点可以丢弃差的应用设计。我们的目标是从Top-N精神疾病应用程序中挖掘用户体验(UX)尺寸,这将有助于为具有严重精神疾病(SMI)和认知赤字的人进行更好的申请。在本文中,我们通过无监督潜在的Dirichlet分析(LDA)从巨大的精神疾病应用程序审查中提取了关键UX维度。最后,LDA揭示了需要考虑精神疾病应用程序设计的20个UX维度,以便通过减少应用最终用户的认知负荷来促进正UX。

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