研究相似性在以任务为中心的在线互动中的作用[36](仅摘要)

D. Cosley, Pamela J. Ludford, L. Terveen
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引用次数: 1

摘要

尽管互联网为社会互动提供了强大的工具,但许多任务——例如,信息搜索——是作为单独的活动进行的。信息寻求者没有意识到,在信息景观中,有一群看不见的人群与他们的路线平行行进。社交导航系统试图让看不见的人群变得可见,而社交推荐系统试图直接介绍人们。然而,当用户专注于一项任务时,他们是否愿意或会对表明其他人存在的社交线索做出反应,目前还不清楚。为了调查这个问题,我们创建了一个在线游戏任务,并配对受试者根据他们对人口统计和兴趣的简短调查的反应来执行任务。我们研究了这些因素如何影响任务结果、互动过程和对伴侣的态度。我们发现,人口统计学上的相似性会影响人们之间的互动方式,尽管这一信息并不明确,而与任务相关的兴趣的相似性或差异性则不会。我们的研究结果为开发社交推荐系统提供了指导方针,并表明需要进一步研究有助于此类系统成功的条件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Studying the effect of similarity in online task-focused interactions[36] (abstract only)
Although the Internet provides powerful tools for social interactions, many tasks-for example, information-seeking-are undertaken as solitary activities. Information seekers are unaware of the invisible crowd traveling in parallel to their course through the information landscape. Social navigation systems attempt to make the invisible crowd visible, while social recommender systems try to introduce people directly. However, it is not clear whether users desire or will respond to social cues indicating the presence of other people when they are focused on a task. To investigate this issue, we created an online game-playing task and paired subjects to perform the task based on their responses to a short survey about demographics and interests. We studied how these factors influence task outcomes, the interaction process, and attitudes towards one's partner. We found that demographic similarity affected how people interact with each other, even though this information was not explicit, while similarities or differences in task-relevant interests did not. Our findings suggest guidelines for developing social recommender systems and show the need for further research into conditions that will help such systems succeed.
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