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用于协作思考的关联链接:通过用户生成的链接在在线问答社区中实现内容的自组织。

Associative linking for collaborative thinking: Self-organization of content in online Q&A communities via user-generated links.

作者信息

Sher Noa, Rafaeli Sheizaf

机构信息

Department of Information and Knowledge Management, University of Haifa, Haifa, Israel.

Shenkar College of Engineering, Design, and Art, Ramat Gan, Israel.

出版信息

PLoS One. 2024 Mar 11;19(3):e0300179. doi: 10.1371/journal.pone.0300179. eCollection 2024.

Abstract

Virtual collaborative Q&A communities generate shared knowledge through the interaction of people and content. This knowledge is often fragmented, and its value as a collective, collaboratively formed product, is largely overlooked. Inspired by work on individual mental semantic networks, the current study explores the networks formed by user-added associative links as reflecting an aspect of self-organization within the communities' collaborative knowledge sharing. Using eight Q&A topic-centered discussions from the Stack Exchange platform, it investigated how associative links form internal structures within the networks. Network analysis tools were used to derive topological indicator metrics of complex structures from associatively-linked networks. Similar metrics extracted from 1000 simulated randomly linked networks of comparable sizes and growth patterns were used to generate estimated sampling distributions through bootstrap resampling, and 99% confidence intervals were constructed for each metric. The discussion-network indicators were compared against these. Results showed that participant-added associative links largely led to networks that were more clustered, integrated, and included posts with more connections than those that would be expected in random networks of similar size and growth pattern. The differences were observed to increase over time. Also, the largest connected subgraphs within the discussion networks were found to be modular. Limited qualitative observations have also pointed to the impacts of external content-related events on the network structures. The findings strengthen the notion that the networks emerging from associative link sharing resemble other information networks that are characterized by internal structures suggesting self-organization, laying the ground for further exploration of collaborative linking as a form of collective knowledge organization. It underscores the importance of recognizing and leveraging this latent mechanism in both theory and practice.

摘要

虚拟协作问答社区通过人和内容的互动产生共享知识。这些知识往往是碎片化的,而其作为集体协作形成的产物的价值在很大程度上被忽视了。受关于个体心理语义网络研究的启发,本研究探索了用户添加的关联链接所形成的网络,以此反映社区协作知识共享中的自组织方面。利用来自Stack Exchange平台的八个以问答主题为中心的讨论,研究了关联链接如何在网络中形成内部结构。使用网络分析工具从关联链接网络中导出复杂结构的拓扑指标度量。从1000个具有可比规模和增长模式的随机链接模拟网络中提取的类似度量,通过自助重采样生成估计抽样分布,并为每个度量构建99%的置信区间。将讨论网络指标与这些指标进行比较。结果表明,参与者添加的关联链接在很大程度上导致网络比具有类似规模和增长模式的随机网络更具聚类性、整合性,并且包含更多连接的帖子。观察到差异会随着时间增加。此外,讨论网络中最大的连通子图被发现是模块化的。有限的定性观察也指出了外部内容相关事件对网络结构的影响。这些发现强化了这样一种观念,即从关联链接共享中产生的网络类似于其他信息网络,其特征是具有暗示自组织的内部结构,为进一步探索协作链接作为一种集体知识组织形式奠定了基础。它强调了在理论和实践中认识和利用这种潜在机制的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9342/10927134/a175c966d3aa/pone.0300179.g001.jpg

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