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An fMRI Exploration of Information Processing in Electronic Networks of Practice1

机译:实践网络中信息处理的功能磁共振成像探索1

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Online forums sponsored by electronic networks of practice have become an important source of information for individuals seeking solutions to problems online. However, not all information available in a forum is helpful or accurate, requiring knowledge seekers to evaluate and filter the solutions they encounter. Most forums offer contextual cues to help knowledge seekers make evaluation decisions, yet little is understood about the cognitive processes and neural mechanisms that underlie how information on these forums is filtered and evaluated. This paper draws on literature in cognitive neuroscience and NeuroIS to develop exploratory research questions about the role of both content and contextual cues in forum filtering tasks, the comparative and interactive effects of different types of contextual cues, and the neural functions associated with filtering processes. These questions are explored using an fMRI experimental study that captured forum information filtering behaviors and measured the neural correlates involved in evaluating both solution content and contextual cues. Results show that both content and contextual cues influence final filtering decisions, with community-based cues factoring more heavily than expert-based cues. Moreover, we observe distinct neural activation patterns when forum knowledge seekers encounter certain cue combinations. Based on our observations, we derive a theoretical model comprising testable research propositions about both behavioral and neural facets of forum information filtering.
机译:电子实践网络主办的在线论坛已经成为个人寻求在线解决问题的重要信息来源。但是,并非论坛中可用的所有信息都是有用的或准确的,因此要求知识寻求者评估和过滤他们遇到的解决方案。大多数论坛都提供了上下文线索来帮助知识寻求者做出评估决策,但是对于认知过程和神经机制的了解却很少,这是如何过滤和评估这些论坛上的信息的基础。本文利用认知神经科学和NeuroIS方面的文献来开发探索性研究问题,涉及内容和上下文提示在论坛过滤任务中的作用,不同类型的上下文提示的比较和交互作用以及与过滤过程相关的神经功能。使用fMRI实验研究探索了这些问题,该研究捕获了论坛信息过滤行为并测量了涉及评估解决方案内容和上下文提示的神经相关因素。结果表明,内容和上下文提示都影响最终的过滤决策,基于社区的提示比基于专家的提示的影响更大。此外,当论坛知识寻求者遇到某些提示组合时,我们观察到不同的神经激活模式。根据我们的观察,我们得出了一个理论模型,该模型包含有关论坛信息过滤的行为和神经方面的可测试研究命题。

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