Affective Dynamics and Control in Group Processes
Affective Dynamics and Control in Group Processes
复制标题
群体过程中的情感动态和控制
DOI：
10.1145/3279981.3279990
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Nagappan, Meiyappan
中科院分区：
文献类型：
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作者：
Hoey, Jesse;Schröder, Tobias;Morgan, Jonathan H.;Rogers, Kimberly B.;Nagappan, Meiyappan
群体的计算建模需要将微观层面与宏观层面的过程和结果联系起来的模型。计算社会科学的最新研究从人类行为的简单模型开始，并试图与社会结构联系起来。然而，这些模型对人类对文化的理解做出了简化的假设，这些假设通常是不现实的，并且可能限制了它们的普遍性。在本文中，我们将贝叶斯影响控制理论作为一个更全面但高度简约的模型，将人工智能，社会心理学和情感整合到一个单一的预测模型中。我们说明这些发展的例子，从一个正在进行的研究项目，旨在计算分析的虚拟软件开发团队。
The computational modeling of groups requires models that connect micro-level with macro-level processes and outcomes. Recent research in computational social science has started from simple models of human behaviour, and attempted to link to social structures. However, these models make simplifying assumptions about human understanding of culture that are of ten not realistic and may be limiting in their generality. In this paper, we present work on Bayesian affect control theory as a more comprehensive, yet highly parsimonious model that integrates artificial intelligence, social psychology, and emotions into a single predictive model of human activities in groups. We illustrate these developments with examples from an ongoing research project aimed at computational analysis of virtual software development teams.