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A Taxonomy of Social Cues for Conversational Agents

机译：对会话代理商的社会案件分类

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Conversational agents (CAs) are software-based systems designed to interact with humans using natural language and have attracted considerable research interest in recent years. Following the Computers Are Social Actors paradigm, many studies have shown that humans react socially to CAs when they display social cues such as small talk, gender, age, gestures, or facial expressions. However, research on social cues for CAs is scattered across different fields, often using their specific terminology, which makes it challenging to identify, classify, and accumulate existing knowledge. To address this problem, we conducted a systematic literature review to identify an initial set of social cues of CAs from existing research. Building on classifications from interpersonal communication theory, we developed a taxonomy that classifies the identified social cues into four major categories (i.e., verbal, visual, auditory, invisible) and ten subcategories. Subsequently, we evaluated the mapping between the identified social cues and the categories using a card sorting approach in order to verify that the taxonomy is natural, simple, and parsimonious. Finally, we demonstrate the usefulness of the taxonomy by classifying a broader and more generic set of social cues of CAs from existing research and practice. Our main contribution is a comprehensive taxonomy of social cues for CM. For researchers, the taxonomy helps to systematically classify research about social cues into one of the taxonomy's categories and corresponding subcategories. Therefore, it builds a bridge between different research fields and provides a starting point for interdisciplinary research and knowledge accumulation. For practitioners, the taxonomy provides a systematic overview of relevant categories of social cues in order to identify, implement, and test their effects in the design of a CA.
机译：会话代理（CAS）是基于软件的系统，旨在使用自然语言与人类互动，并在近年来吸引了相当大的研究兴趣。在计算机之后是社交行为者范例，许多研究表明，人类在展示小型谈话，性别，年龄，手势或面部表情等社会案例时，人类会对CA作出社会反应。但是，对CA的社会线索的研究分散在不同的领域，通常使用他们的特定术语，这使得识别，分类和积累现有知识来挑战。为了解决这个问题，我们进行了系统的文献综述，以确定来自现有研究的CA的初始社会线索。从人际通信理论的分类建立，我们开发了一种分类，将所确定的社会线索分为四大类（即口头，视觉，听觉，隐形）和十个子类别。随后，我们评估了使用卡分拣方法所确定的社会提示和类别之间的映射，以验证分类学是自然的，简单的，简单的。最后，我们通过对现有的研究和实践进行分类，通过对CAS的更广泛和更通用的社会线索集进行分类，展示了分类法。我们的主要贡献是厘米的社会线索的全面分类。对于研究人员来说，分类学有助于系统地将社会线索的研究分类为分类学的类别和相应的子类别之一。因此，它建立了不同研究领域之间的桥梁，并为跨学科研究和知识积累提供了一个起点。对于从业者，分类学提供了有关相关类别的社会提示的系统概述，以确定，实施和测试它们在CA的设计中的影响。

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