网络亲和空间中关键参与者的知识共享话语类型

IF 1.6 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE Information and Learning Sciences Pub Date : 2021-06-18 DOI:10.1108/ILS-09-2020-0211
Priya Sharma, Qiyuan Li, Susan M. Land
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引用次数: 1

摘要

在线社交网站的增长及其作为亲和空间的概念化使其非常适合探索个人如何围绕特定兴趣或亲和分享知识和实践。本研究的目的是扩展对在线亲密空间中高度活跃/关键参与者的了解,特别是他们维持和促进知识共享的方式。设计/方法/方法本研究分析了514篇从一个在线亲和力空间收集的关于疾病管理的讨论帖子。本研究使用了多种方法来回答研究问题:作者使用话语分析来检查在线亲和空间中的对话,使用社会网络分析来识别空间中的参与结构,使用关联规则挖掘和情感分析来识别讨论的话语代码和情感共现。研究结果表明,关键角色和其他角色的话语质量和类型差异很大。关键角色在网络中的话语是用来阐述和解释想法和概念的,而其他角色则提供更多的支持性角色,主要参与讲故事。独创性/价值本工作通过识别关键行为者特有的特定话语类型和知识共享类型,扩展了非正式指导和关键行为者在亲密空间中的作用。此外,本研究还提供了一个使用规则挖掘关联和情感分析相结合来表征亲和空间性质的示例。
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Knowledge sharing discourse types used by key actors in online affinity spaces
Purpose The growth of online social network sites and their conceptualization as affinity spaces makes them well suited for exploring how individuals share knowledge and practices around specific interests or affinities. The purpose of this study is to extend what is known about highly active/key actors in online affinity spaces, especially the ways in which they sustain and contribute to knowledge sharing. Design/methodology/approach This study analyzed 514 discussion posts gathered from an online affinity space on disease management. This study used a variety of methods to answer the research questions: the authors used discourse analyses to examine the conversations in the online affinity space, social network analyses to identify the structure of participation in the space and association rule mining and sentiment analysis to identify co-occurrence of discourse codes and sentiment of the discussions. Findings The results indicate that the quality and type of discourse varies considerably between key and other actors. Key actors’ discourse in the network serves to elaborate on and explain ideas and concepts, whereas other actors provide a more supportive role and engage primarily in storytelling. Originality/value This work extends what is known about informal mentoring and the role of key actors within affinity spaces by identifying specific discourse types and types of knowledge sharing that are characteristic of key actors. Also, this study provides an example of the use of a combination of rule mining association and sentiment analysis to characterize the nature of the affinity space.
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来源期刊
Information and Learning Sciences
Information and Learning Sciences INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
9.50
自引率
2.90%
发文量
30
期刊介绍: Information and Learning Sciences advances inter-disciplinary research that explores scholarly intersections shared within 2 key fields: information science and the learning sciences / education sciences. The journal provides a publication venue for work that strengthens our scholarly understanding of human inquiry and learning phenomena, especially as they relate to design and uses of information and e-learning systems innovations.
期刊最新文献
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