We describe a computational model of social norms based on identifying values that a certain culture finds desirable such as dignity, generosity and politeness. The model quantifies these values in the form of Culture-Sanctioned Social Metrics (CSSMs) and treats social norms as the requirement to maximize these metrics from the perspective of the self, peers and public. This model can be used to create realistic social simulations, to explain or predict human behavior in specific scenarios, or as a component of robots or agents that need to interact with humans in specific social-cultural settings. We validate the model by using it to represent a complex deception scenario and showing that it can yield non-trivial insights such as the explanation of apparently irrational human behavior.
A theory of social and cultural behavior strongly related to social norms is Brown and Levinson's politeness theory @cite_35 , which centers around the maintenance of face'' defined as the public self-image of the adult human. More specifically, they define the positive face'' that refers to one's self esteem and the negative face'' that refers to one's freedom to act. While the Brown-Levinson model aims to discover the culture-independent universals in human communication, it is clear that their definition of politeness does not necessarily match the definition of politeness and indeed the desirable behavior in specific cultures. While indirect speech might help preserve face, there are cultures where direct speech is considered polite and desirable. The interpretation of the Brown-Levinson model in the context of specific cultures is a significant ongoing research topic @cite_25 @cite_1 .
@cite_35 @cite_1 @cite_25
1996209594 2151667087 1506679937 2157163421
Abstract This paper is a critical examination of the theory of linguistic politeness proposed by Brown and Levinson (1978, 1987). The paper focuses on the notion, fundamental to their theory, of ‘face’, and questions the universality of the proposed constituents of ‘face’ in the light of the Japanese language and culture. First, results from anthropological studies on Japanese society are presented to illustrate the discrepancy between Brown and Levinson's assumption and the Japanese notion of ‘face’, Secondly, linguistic evidence is given that Brown and Levinson's theory provides wrong predictions for Japanese politeness phenomena. Examples are drawn from formulaic expressions, honorifics and the verbs of giving and receiving. One conclusion from these observations is that a universal theory of linguistic politeness must take into account at a more fundamental level the cultural variability in the constituents of ‘face’. A central source of cultural differences is the communication of politeness, which can powerfully affect perception and behavior. Our computational adaptation of a universal theory of human politeness (from Brown and Levinson, 1987) combines culture-specific aspects of social context to generate expectations, score, interpret and recommend polite and impolite behaviors. Tests show this approach could reduce software development costs and increase an intelligent agent's behavior repertoire through the incorporation of modular, cross-cultural etiquette libraries. We argue that traditional cultural factors models (from Hofstede, Nisbett, etc.) are too abstract to provide good predictions of important human performance behaviors such as directive compliance. Instead, we focus on culture-specific social interaction behaviors (i.e., "etiquette") as a bridge between abstract cultural factors and human performance. We describe a computational model of etiquette and politeness perception, called CECAEDA (Computational Effects of Cultural Attributes and Etiquette on Directive Adherence). CECAEDA consists of four parts: (1) a culturally universal model of politeness perceptions, their causes and effects, (2) a culturally universal cognitive model compliance decision making and behaviors, (3) a set of hypotheses about how politeness perceptions alter directive compliance, and (4) a set of hypotheses about how cultural factors (specifically, those proposed by Hofstede [1]) affect etiquette perceptions and, thus, directive compliance in culture-specific ways. Each component is discussed in detail, followed by a brief presentation of our research test bed and paradigm for evaluating CECAEDA. We propose a computational framework for identifying linguistic aspects of politeness. Our starting point is a new corpus of requests annotated for politeness, which we use to evaluate aspects of politeness theory and to uncover new interactions between politeness markers and context. These findings guide our construction of a classifier with domain-independent lexical and syntactic features operationalizing key components of politeness theory, such as indirection, deference, impersonalization and modality. Our classifier achieves close to human performance and is effective across domains. We use our framework to study the relationship between politeness and social power, showing that polite Wikipedia editors are more likely to achieve high status through elections, but, once elevated, they become less polite. We see a similar negative correlation between politeness and power on Stack Exchange, where users at the top of the reputation scale are less polite than those at the bottom. Finally, we apply our classifier to a preliminary analysis of politeness variation by gender and community.