An Interpretable Deep Learning Approach to Understand Health Misinformation Transmission on YouTube

2022 | HICSS | Citations: 0

Authors: Xie, Jiaheng; Chai, Yidong; Liu, Xiao

Abstract: Health misinformation on social media devastates physical and mental health, inv ... Expand

Abstract: Health misinformation on social media devastates physical and mental health, invalidates health gains, and potentially costs lives. Deep learning methods have been deployed to predict the spread of misinformation, but they lack the interpretability due to their blackbox nature. To remedy this gap, this study proposes a novel interpretable deep learning, Generative Adversarial Network based Piecewise Wide and Attention Deep Learning (GAN-PiWAD), to predict health misinformation transmission in social media. GANPiWAD captures the interactions among multi-modal data, offers unbiased estimation of the total effect of each feature, and models the dynamic total effect of each feature. Interpretation of GAN-PiWAD indicates video description, negative video content, and channel credibility are key features that drive viral transmission of misinformation. This study contributes to IS with a novel interpretable deep learning that is generalizable to understand human decisions. We provide direct implications to design interventions to identify misinformation, control transmissions, and manage infodemics. Collapse

Topics: misinformation YouTube social media web page media richness

Methods: deep learning generative adversarial network machine learning method machine learning parametric test

Theories: social exchange theory media richness theory

How does IT Occupational Culture Affect Knowledge Sharing in Organizations?

2020 | Communications of the Association for Information Systems | Citations: 0

Authors: Zhao, Yu (Audrey); Srite, Mark

Abstract: In this study, we investigate the relationship between the occupational culture ... Expand

Abstract: In this study, we investigate the relationship between the occupational culture of information technology (IT) personnel and knowledge sharing in organizations. We suggest that some elements of IT occupational culture affect knowledge sharing among IT personnel and business end users. Drawing on cultural psychology, we present one possible approach through which IT occupational culture manifests through six elements of organizational structure (i.e., stories, symbols, power structures, control systems, and rituals and routines) and affects the knowledge-sharing process. In doing so, we better understand behaviors related to knowledge sharing and IT diffusion in organizations beyond the limitations of previous IT-diffusion studies. Collapse

Topics: IT workforce knowledge sharing technology diffusion organization structure IT governance

Methods: partial least squares regression survey partial least squares path modeling structural equation modeling PLS tool

Theories: trust theory social exchange theory social network theory organizational behavior theory media richness theory

TARGETS' PRACTICES: HOW PEOPLE ALLOCATE THEIR ATTENTION AMONG MULTIPLE STREAMS OF INCOMING INFORMATION

2012 | European Conference On Information Systems | Citations: 0

Authors: Turner, Jeanine; O'Leary, Michael

Abstract: The communication environment within organizations provides multiple opportuniti ... Expand

Abstract: The communication environment within organizations provides multiple opportunities for informational retrieval throughout the day. While previous research has explored media choice from a sender’s perspective, little research has explored the choices receivers or targets make in attending to messages and information streams. This paper explores the process that targets use to evaluate messages by introducing a model of target attention allocation. Built on theories of media choice, uses and gratifications, and social exchange, this model focuses on targets’ need to reduce uncertainty, the interactivity offered by the media available to them, and the social norms guiding their media choices. In doing so, the model provides a means for measuring targets’ willingness to remain focused on a given information stream or, conversely, switch to another information stream. Collapse

Topics: social norm decision making social influence mobile system media richness

Theories: media richness theory social exchange theory social presence theory