A tune-attention model for information sharing behaviour on social media

Zaid Amin (P90515)

Please use this identifier to cite or link to this item: https://ptsldigital.ukm.my/jspui/handle/123456789/520402

Full metadata record

DC Field	Value	Language
dc.contributor.advisor	Nazlena Mohamad Ali, Assoc. Prof. Dr.	-
dc.contributor.author	Zaid Amin (P90515)	-
dc.date.accessioned	2023-10-18T03:49:35Z	-
dc.date.available	2023-10-18T03:49:35Z	-
dc.date.issued	2022-03-02	-
dc.identifier.other	ukmvital:128792	-
dc.identifier.uri	https://ptsldigital.ukm.my/jspui/handle/123456789/520402	-
dc.description	Having attentive behaviour when receiving and sharing information on social media is essential. Through this attentive behavior, users are more likely to consume factual information with constructive purposes. Users can effectively identify misinformation so that they are not affected by the latent misleading contained. In fact, through the vast digital growing information in the omnipresence of social media today, increasing behavioral problems stemming from our one-click habit of easy decisions are blatantly faster than bots through propagating misinformation. This spread of misinformation literally can do serious damage to individuals and society in general. However, although many kinds of research explored traceability and situation prediction on spreading misinformation, more research is required to prevent and understand the issue of distraction on human attention. Questions arise on how such technological intervention can significantly handle the lack of users visual abilities and gain accuracy when deciding to share information. This study aims to identify key factors that trigger and influence users' attention in information sharing, develop new models and user interfaces based on the attention-based design in information sharing, and evaluate the effectiveness of the developed models. This study uses a mixture of quantitative and qualitative methods. Our work began in Study 1 by investigating main (five constructs) that highly influence users' behavior in sharing information. Then, In Study 2 and 3, we developed and experimenting with Implicit Association Test (IAT) and Visual Selective Attention System (VSAS) using an attention-based design approach. The findings suggested that attention-based design significantly influences user decisions on sharing information. Lastly, based on this finding, we estimate in Study 4 the overall and the structural model fit relationship between the main (five constructs) using the multivariate model analysis with the Structural Equation Modeling (SEM) procedure. The result is that the Tune-Attention Model shows that all data are significantly valid and reliable in each model relationship. We conclude that the intervention improved user choices about information that they share on social media. The realization of engaging attentive behavior in sharing information is expected to reduce the spread of misinformation. Furthermore, attentive behavioral factors are needed to form the basis of developing interactions into the design of future social media application systems, which can avoid the potential harm caused by sharing misinformation.,Ph.D.	-
dc.language.iso	eng	-
dc.publisher	UKM, Bangi	-
dc.relation	Institute of Visual Informatics/ Institut Informatik Visual (IVI)	-
dc.rights	UKM	-
dc.subject	Universiti Kebangsaan Malaysia -- Dissertations	-
dc.subject	Dissertations, Academic -- Malaysia	-
dc.subject	Information sharing	-
dc.subject	Social media	-
dc.title	A tune-attention model for information sharing behaviour on social media	-
dc.type	Theses	-
dc.format.pages	203	-
Appears in Collections:	Institute of Visual Informatics/ Institut Informatik Visual (IVI)

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