The Interpersonal Effects of Emotions in Money versus Candy Games

Emotional expressions significantly influence perceivers’ behavior in economic games and negotiations. The current research examined the interpersonal effects of emotions when such information cannot be used to guide behavior for increasing personal gain and when monetary rewards are made salient. For this, a one-shot Public Goods Game (Studies 1, 2, and 3) and Dictator Game (Studies 4 and 5) were employed, in which the dominant strategy to maximize personal payoff is independent from the counterplayers’ intention signaled through their facial expressions (happiness, sadness, and anger). To elicit a monetary mindset, we used money (vs. candy) as the mode of exchange in the games with (Studies 1 and 2) or without (Studies 3, 4, and 5) additional contextual framing (i.e. Wall Street Game vs. Community Game). Across five studies (N = 1211), participants were found to be more generous towards happy and sad targets compared to angry ones. Such behavioral response based on emotional information was accounted for by the trait impressions (i.e. likability, trustworthiness) formed of the counterplayer. This effect was significantly reduced when money acted as the mode of exchange, thereby making participants focus more on their selfgain. Together, the findings extend previous work by highlighting the social functional role of emotions in human exchange and its moderation by money as a transaction medium

Presenting in Virtual Worlds: Towards an Architecture for a 3D Presenter explaining 2D-Presented Information

Entertainment, education and training are changing because of multi-party interaction technology. In the past we have seen the introduction of embodied agents and robots that take the role of a museum guide, a news presenter, a teacher, a receptionist, or someone who is trying to sell you insurances, houses or tickets. In all these cases the embodied agent needs to explain and describe. In this paper we contribute the design of a 3D virtual presenter that uses different output channels to present and explain. Speech and animation (posture, pointing and involuntary movements) are among these channels. The behavior is scripted and synchronized with the display of a 2D presentation with associated text and regions that can be pointed at (sheets, drawings, and paintings). In this paper the emphasis is on the interaction between 3D presenter and the 2D presentation

The Influence of Emotion Expression on Perceptions of Trustworthiness in Negotiation

When interacting with computer agents, people make inferences about various characteristics of these agents, such as their reliability and trustworthiness. These perceptions are significant, as they influence people’s behavior towards the agents, and may foster or inhibit repeated interactions between them. In this paper we investigate whether computer agents can use the expression of emotion to influence human perceptions of trustworthiness. In particular, we study human-computer interactions within the context of a negotiation game, in which players make alternating offers to decide on how to divide a set of resources. A series of negotiation games between a human and several agents is then followed by a “trust game.” In this game people have to choose one among several agents to interact with, as well as how much of their resources they will trust to it. Our results indicate that, among those agents that displayed emotion, those whose expression was in accord with their actions (strategy) during the negotiation game were generally preferred as partners in the trust game over those whose emotion expressions and actions did not mesh. Moreover, we observed that when emotion does not carry useful new information, it fails to strongly influence human decision-making behavior in a negotiation setting.Engineering and Applied Science

Designing a Story Database for Use in Automatic Story Generation

In this paper we propose a model for the representation of stories in a story database. The use of such a database will enable computational story generation systems to learn from previous stories and associated user feedback, in order to create believable stories with dramatic plots that invoke an emotional response from users. Some of the distinguishing characteristics of our proposal are the inclusion of what we call ‘narratological concepts’ and user feedback in the story database

Interpersonal effects of expressed anger and sorrow in morally charged negotiation

The expression of emotion can play a significant role in strategic decision-making. In this study, we hypothesized that emotion expression alters behavior in morally charged negotiation. We investigated the impact of facial displays of discrete emotions, specifically anger and sadness, in a morally charged multi-issue negotiation task. Our results indicate that if a negotiator associated moral significance to the object of the negotiation, displays of anger resulted in reduced concession making whereas displays of sadness increased concession making. Moral significance of the issues fostered an emotional matching mechanism of sorrow, where a sorrow expression from one party elicited a sorrow expression from the other. Taken together, the results indicate that emotional expressions can affect morally charged negotiation in ways that can inhibit as well as promote cooperation

Generating socially appropriate tutorial dialog

Analysis of student-tutor coaching dialogs suggest that good human tutors attend to and attempt to influence the motivational state of learners. Moreover, they are sensitive to the social face of the learner, and seek to mitigate the potential face threat of their comments. This paper describes a dialog generator for pedagogical agents that takes motivation and face threat factors into account. This enables the agent to interact with learners in a socially appropriate fashion, and foster intrinsic motivation on the part of the learner, which in turn may lead to more positive learner affective states

An Agent-Based Model of Collective Emotions in Online Communities

We develop a agent-based framework to model the emergence of collective emotions, which is applied to online communities. Agents individual emotions are described by their valence and arousal. Using the concept of Brownian agents, these variables change according to a stochastic dynamics, which also considers the feedback from online communication. Agents generate emotional information, which is stored and distributed in a field modeling the online medium. This field affects the emotional states of agents in a non-linear manner. We derive conditions for the emergence of collective emotions, observable in a bimodal valence distribution. Dependent on a saturated or a superlinear feedback between the information field and the agent's arousal, we further identify scenarios where collective emotions only appear once or in a repeated manner. The analytical results are illustrated by agent-based computer simulations. Our framework provides testable hypotheses about the emergence of collective emotions, which can be verified by data from online communities.Comment: European Physical Journal B (in press), version 2 with extended introduction, clarification