Visualizing social links in exploratory search

Justin Donaldson, Michael D. Conover, Benjamin Markines, Heather Roinestad, F. Menczer
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引用次数: 15

Abstract

The visualization of results is a critical component in search engines, and the standard ranked list interface has been a consistently predominant model. The emergence of social media provides a new opportunity to investigate visualization techniques that expose socially derived links between objects to support their exploration. Here we introduce and evaluate network-based visualizations for facilitating the exploration of a Web knowledge space. We developed a force directed network interface to visualize the result sets provided by GiveALink.org, a social bookmarking site. The classifications and tags by users are aggregated to build a social similarity network between bookmarked resources. We administered a user study to evaluate the potential of leveraging such social links in an exploratory search task. During exploration, the similarity links are used to arrange the resources in a semantic layout. Users in our study prefer a hybrid interface combining a conventional ranked list and a two dimensional network map, allowing them to find the same amount of relevant information using fewer queries. This behavior is a direct result of the additional structural information present in the network visualization, which aids them in the exploration of the information space.
探索式搜索中的社交链接可视化
搜索结果的可视化是搜索引擎的重要组成部分,而标准的排序列表界面一直是主流模式。社交媒体的出现为研究可视化技术提供了一个新的机会,这种技术可以揭示对象之间的社交链接,从而为探索对象提供支持。在此,我们介绍并评估了基于网络的可视化技术,以促进对网络知识空间的探索。我们开发了一个力定向网络接口,用于可视化社会书签网站 GiveALink.org 提供的结果集。通过汇总用户的分类和标签,可以在书签资源之间建立一个社会相似性网络。我们进行了一项用户研究,以评估在探索性搜索任务中利用这种社交链接的潜力。在探索过程中,相似性链接被用于在语义布局中排列资源。在我们的研究中,用户更喜欢传统的排序列表和二维网络地图相结合的混合界面,这样他们就能用更少的查询次数找到相同数量的相关信息。这种行为是网络可视化中存在的额外结构信息的直接结果,这些信息有助于他们探索信息空间。
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