Abstract
The rapid growth of the phenomenon of Online Social Networks (OSN) has had a revolutionary impact on human decision-making (DM). It is apparent that OSN play an important role in supporting different types of DM, as they provide their users with various forms of support, ranging from instrumental and informational to emotional. The risk comes from the use of irrelevant or inaccurate information or from misunderstanding relevant information. DM behavior of OSN users and their cognitive processes are not understood well by OSN creators, designers and providers. The capabilities of OSN platforms are not leveraged sufficiently to support the complexities of DM. The key objective of this paper is to propose recommendations on how OSN can be modeled, designed and implemented in such a way that leverages the wisdom of crowds to support effective decision making. We propose an architecture that has distinctive spaces and support for modelling and conversations.
Recommended Citation
Sadovykh, Valeria Aleksandra and Sundaram, David, "Online Social Networks Decision Support Architecture: Spaces for Modelling and Conversations" (2019). AMCIS 2019 Proceedings. 11.
https://aisel.aisnet.org/amcis2019/adv_info_systems_research/adv_info_systems_research/11
Online Social Networks Decision Support Architecture: Spaces for Modelling and Conversations
The rapid growth of the phenomenon of Online Social Networks (OSN) has had a revolutionary impact on human decision-making (DM). It is apparent that OSN play an important role in supporting different types of DM, as they provide their users with various forms of support, ranging from instrumental and informational to emotional. The risk comes from the use of irrelevant or inaccurate information or from misunderstanding relevant information. DM behavior of OSN users and their cognitive processes are not understood well by OSN creators, designers and providers. The capabilities of OSN platforms are not leveraged sufficiently to support the complexities of DM. The key objective of this paper is to propose recommendations on how OSN can be modeled, designed and implemented in such a way that leverages the wisdom of crowds to support effective decision making. We propose an architecture that has distinctive spaces and support for modelling and conversations.