Information about audiences influence how speakers produce messages, biasing speakers’ own later recall (Higgins & Rholes, 1978), contingent on the creation of a shared reality between interlocutors (Echterhoff, Higgins, & Rholes, 2005). We tested for a similar effect within third party dialogue comprehension, in which overheard addressees displayed evaluative backchannel responses. Participants observed an interaction containing valenceambiguous personal information, and were later asked to recall the information and make related judgments. Addressees either responded positively or negatively to the speaker’s description. Across three experiments, we found that addressee responses biased recall when the responses were cues to a shared perspective, either due to the collaborative construction of the talk or prior shared knowledge between speaker and addressee. Addressee responses as cues to the addressee’s stance alone did not bias overhearer recall. These findings support the argument that perception of a shared reality is a central component of dialogue comprehension.

Designing virtual characters that are capable of conveying a sense of personality is important for generating realistic experiences, and thus a key goal in computer animation research. Though the influence of gesture and body motion on personality perception has been studied, little is known about which attributes of hand pose and motion convey particular personality traits. Using the "Big Five" model as a framework for evaluating personality traits, this work examines how variations in hand pose and motion impact the perception of a character's personality. As has been done with facial motion, we first study hand motion in isolation as a requirement for running controlled experiments that avoid the combinatorial explosion of multimodal communication (all combinations of facial expressions, arm movements, body movements, and hands) and allow us to understand the communicative content of hands. We determined a set of features likely to reflect personality, based on research in psychology and previous human motion perception work: shape, direction, amplitude, speed, and manipulation. Then we captured realistic hand motion varying these attributes and conducted three perceptual experiments to determine the contribution of these attributes to the character's personalities. Both hand poses and the amplitude of hand motion affected the perception of all five personality traits. Speed impacted all traits except openness. Direction impacted extraversion and openness. Manipulation was perceived as an indicator of introversion, disagreeableness, neuroticism, and less openness to experience. From these results, we generalize guidelines for designing detailed hand motion that can add to the expressiveness and personality of characters. We performed an evaluation study that combined hand motion with gesture and body motion. Even in the presence of body motion, hand motion still significantly impacted the perception of a character's personality and could even be the dominant factor in certain situations.

Personality can be assessed with standardized inventory questions with scaled responses such as "How extraverted is this character?" or with open-ended questions assessing first impressions, such as "What personality does this character convey?" Little is known about how the two methods compare to each other, and even less is known about their use in the personality assessment of virtual agents. We tested what personality virtual agents conveyed through gesture alone when the agents were programmed to display introversion versus extraversion (Experiment 1) and high versus low emotional stability (Experiment 2). In Experiment 1, both measures indicated participants perceived the extraverted agent as extraverted, but the open-question technique highlighted the perception of both agents as highly agreeable whereas the inventory indicated that the extraverted agents were also perceived as more open to new experiences. In Experiment 2, participants perceived agents expressing high versus low emotional stability differently depending on assessment style. With inventory questions, the agents differed on both emotional stability and agreeableness. With the open-ended question, participants perceived the high stability agent as extraverted and the low stability agent as disagreeable. Inventory and open-ended questions provide different information about what personality virtual agents convey and both may be useful in agent development.