用小群体理论分析社会计算需求

A. Sutcliffe
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引用次数: 3

摘要

社会心理学中的小团体理论和HCI b[4]研究中产生的社会技术系统分析方法等理论可以有效地应用于RE实践。本文介绍了小群体作为复杂系统理论作为社会心理学研究的新资源。SGCAS理论的优势在于它在社会心理学研究中的折衷主义基础,以及它用模型理论的方法将社会学问题形式化。相比之下,分布式认知[15]和活动理论[16]都更强调人类与世界上的人工制品的相互作用。SGCAS理论可以解释任务-代理-工具网络中的这些问题,并提供了在更丰富的群体互动社会观点中对技术贡献进行建模的方法。小群体理论的应用仅限于目标导向的协作系统(即CSCW),这可能会限制其规模。然而,大多数以工作为导向的社会系统,除了最近对“群体智慧”的兴趣之外,在任务组织中都有一个固有的等级结构。因此,SGCAS可以扩展到电子科学的大规模协作,因为更大规模协作中的团队需求将是相似的。SGCAS理论提供了一个可再生能源社会系统问题可以表达的建模框架。首先,它可以作为一种诊断工具,发现社会技术系统中的潜在问题;其次,它可以作为社会问题的来源,与i*模型相结合,为改善可再生能源提供关键的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysing social computing requirements with small group theory
Theories such as Small Group theory from social psychology and methods for socio-technical systems analysis which arose from research in HCI [4] can be usefully applied to RE practice. This paper has introduced the theory of Small Groups as Complex Systems [5] as a new resource for RE. The strength of SGCAS theory lies in its eclectic foundations in social psychology research, and its formalisation of sociological issues with a model theoretic approach. In contrast, Distributed Cognition [15] and Activity theory [16] both place more emphasis on human interaction with artefacts in the world. SGCAS theory can account for these issues in the task-agent-tool network, and provides the means of modelling the contribution of technology within a much richer social view of group interaction. Application of Small Group theory is limited to goal oriented collaborative systems (i.e. CSCW) with small groups, which may appear to limit its scale. However, most work oriented social systems, apart from the recent interest in ‘wisdom of crowds’ example, have a hierarchical structure inherent in the organisation of tasks. SGCAS can therefore scale to large scale collaborations in e-science since the requirements of teams within the larger scale collaboration will be similar. SGCAS theory provides a modelling framework within which RE social systems issues can be expressed. It could be used first as a diagnostic instrument to find potential problems in socio-technical systems and, secondly, as a source of social issues that can be combined with i* models to provide critical insight for improving RE.
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