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Evaluation of Social Media Collaboration Using Task-Detection Methods

机译:使用任务检测方法评估社交媒体合作

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Collaboration using social media is a good way of jointly constructing knowledge. This study aims at better understanding collaborative knowledge construction processes by applying innovative (micro-)task detection approaches. We take a closer look at the interactions of a user with a shared digital artifact by analyzing the captured interaction data. The goal is to identify domain-independent interaction patterns, which can serve as indicators for knowledge development (operationalized as accommodation). We designed an empirical study under laboratory conditions that used our method. The applied task detection approach identified accommodation with a rate of 77.63% without resorting to textual features. This result instantiates an improvement as compared to a previous study in which the text in focus was identified as the feature with best discriminative power. We discuss our hypothesis that our method is independent from the used knowledge domain.
机译:使用社交媒体进行协作是共同构建知识的好方法。这项研究旨在通过应用创新的(微)任务检测方法,更好地理解协作知识的构建过程。通过分析捕获的交互数据,我们仔细研究了用户与共享数字工件之间的交互。目的是确定与领域无关的交互模式,这些模式可以用作知识发展的指标(可作为适应性操作)。我们在实验室条件下使用我们的方法设计了一项经验研究。应用的任务检测方法识别出的调适率为77.63%,而没有诉诸文字特征。与先前的研究(其中重点突出的文本被确定为具有最佳判别力的特征)相比,该结果可显示出一种改进。我们讨论我们的方法独立于所使用的知识领域的假设。

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