Can a Virtual Cat Persuade You? The Role of Gender and Realism in Speaker Persuasiveness

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1 Can a Virtual Cat Persuade You? The Role of Gender and Realism in Speaker Persuasiveness Catherine Zanbaka 1, Paula Goolkasian 2, Larry F. Hodges 1 1 Department of Computer Science University of North Carolina at Charlotte Charlotte, NC {czanbaka, lfhodges}@uncc.edu 2 Department of Psychology University of North Carolina at Charlotte Charlotte, NC pagoolka@uncc.edu ABSTRACT This study examines the roles of gender and visual realism in the persuasiveness of speakers. Participants were presented with a persuasive passage delivered by a male or female person, virtual human, or virtual character. They were then assessed on attitude change and their ratings of the argument, message, and speaker. The results indicated that the virtual speakers were as effective at changing attitudes as real people. Male participants were more persuaded when the speaker was female than when the speaker was male, whereas female participants were more persuaded when the speaker was male than when the speaker was female. Cross gender interactions occurred across all conditions, suggesting that some of the gender stereotypes that occur with people may carry over to interaction with virtual characters. Ratings of the perceptions of the speaker were more favorable for virtual speakers than for human speakers. We discuss the application of these findings in the design of persuasive human computer interfaces. AUTHOR KEYWORDS Virtual humans, virtual characters, human-computer interaction, persuasion, gender, experimental studies ACM CLASSIFICATION KEYWORDS H.5.1. [Information Interfaces and Presentation]: Multimedia Information Systems - Artificial, augmented, and virtual realities, Evaluation/methodology. INTRODUCTION Virtual characters, also referred to as avatars, synthetic characters, or agents, are 3D representations of an existing Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. CHI 2006, April 22 27, 2006, Montréal, Québec, Canada. Copyright 2006 ACM /06/ $5.00. system. Virtual characters act as a new medium to interact with system information. Advances in photo-realistic rendering, processor speeds, as well as high-quality graphics cards make the use of virtual characters for various types of interfaces possible. Virtual characters can be helpful for technical training (e.g. nurses, medical students, actors, technicians, etc), social skills training (e.g. practicing your presentation skills, job interview skills, and countless other social skills), tele-collaboration, and enhancing interfaces and virtual environments. In addition, the gender, age, race, physical attractiveness, attire, or even species of a virtual character can be altered in a matter of minutes to match the needs at hand. In order to successfully exploit virtual humans for these various training applications, especially where social interaction plays an important role, researchers must first determine if there exists a measurable similarity between a person s response to a virtual character and that person s response to a real person. The CASA (Computers are Social Actors) paradigm states that people apply social rules to computers [14]. In this study, we apply the CASA paradigm to investigate the persuasiveness of virtual speakers. In particular, we are interested in how the gender and realism of a virtual character affect the degree of influence. The approach of the CASA paradigm is to pick a social science theory which concerns human social behavior, replace the human role with a computer, provide the computer with human-like characteristics, and determine if the social rule still applies. This paradigm also states that theories of human-human interaction from social psychology literature are relevant to the field of humancomputer interaction (HCI) and have clear implications for user interface design [15]. Following the CASA paradigm, we investigated one of the classical tests of human-human interaction from social psychology literature. In particular, this study deals with persuasion which has a long history in terms of its impact on theories of social influence [20]. We examined the role of gender and realism in the persuasiveness of virtual characters by directly comparing virtual characters with real humans. 1153

2 RELATED WORKS Persuasion Persuasion, also referred to as attitude change, is an example of social influence. Persuasion occurs when one person attempts to induce change in the beliefs, attitudes, or behavior of another person or a group of people. There are many factors that influence persuasion, including the strength of the argument [20], the source of the message [3, 21], and the person being influenced [3, 5]. For instance, Carli showed that female speakers who spoke more tentatively were more influential with male listeners and less influential with female listeners than those who spoke more assertively. Male speakers, on the other hand, were equally influential with both men and women listeners [3]. Men are regarded as more dominant and influential than women. Men are also seen as more effective leaders than women. Finally, there is a tendency for females to be more easily persuaded than men, especially when the speaker is male [5]. Mullennix, et al., conducted a study which investigated whether social perception of human speech and computerized text-to-speech (TTS) is affected by gender of voice and gender of listener. Listeners were presented with a persuasive argument in either male or female human or synthetic voice and were assessed on attitude change and their ratings of various speech qualities. They found that the degree of persuasion did not differ across human and synthetic speech, but that female listeners were more persuaded than male listeners. Female human speech was rated as preferable to female synthetic speech and male synthetic speech was rated as preferable to female synthetic speech. They also found that the patterns of rating across male and female listeners were fairly similar across human and synthetic speech [11]. In a previous study, Stern, et al., also found that the male human voice was perceived more favorable than the computer synthesized voice and the speaker was perceived more favorably when the voice was human than when it was computer synthesized. However, they found no evidence that computerized speech, as compared with human voice, affected degree of persuasion [25]. These studies focused on the speech quality of the persuasive message, the focus of our study is on the visual quality of the speaker delivering the persuasive argument. Humans and Computers Researchers have shown that people interact, treat, and identify with computers and software agents based on perceived, human characteristics, such as the computer s helpfulness, expertise, and friendliness [22]. Nass, et al., conducted a study which investigated whether computers ingrained with minimal gender cues evoke gender-based stereotypic responses. They were able to elicit gender stereotyping from computers with voice output, providing evidence that the tendency to gender stereotype is strong and extends even to machines [14]. In another study, Nass and colleagues examined whether people would interpret and respond to paralinguistic personality cues in computer generated speech in the same way as they do human speech [12]. They found that participants accurately recognized personality cues in TTS and showed strong similarity-attraction effects. That is, when the personality of the computer matched their own personality, participants regarded the computer voice more attractive, credible, and informative. Participants were also more likely to buy a product from a computer that matched their personality [12]. Building on this research, we examined how other characteristics of computers influence human-computer interaction. In particular, we were interested in the effects of the gender and realism of computer synthesized characters on persuasion. Anthropomorphic Agents Avatars are used in various applications including, but not limited to, virtual environments [19, 23], instant messaging systems (e. g. Yahoo Messenger: online role-playing games (e.g. World of Warcraft: and even word processors (e. g. Microsoft Word). The inclusion of avatars in these applications is intended to enhance the user experience. One assumption is that the degree of anthropomorphism of the avatar influences the user's perceptions of the avatar [17]. Anthropomorphism has been defined as the extent to which a character has either the appearance or behavioral attributes of humans [16]. In this paper, we are more interested in the visual rather than the behavioral component of anthropomorphism. Researchers have shown that an anthropomorphic agent on a Web site can increase a sense of social presence and telepresence. The increased sense of presence resulted in more favorable attitudes towards the advertisement in the Web site and a stronger intention to revisit the site [4]. Koda and Maes [10] argue that employing a face as the representation of an agent is engaging, makes a user pay more attention, and takes more effort for a user to interact with the system. They also found that realistic faces were better liked and rated more intelligent than abstract faces by the users. On the other hand, in a study that examined the influence of anthropomorphism and perceived agency on presence, copresence, and social presence in a virtual environment, researchers found that participants interacting with the less anthropomorphic image reported more copresence and social presence than those interacting with partners represented by either no image at all or by a highly anthropomorphic image [16]. This result may be due to higher expectations set up by realistic avatars, which may 1154

3 lead to disappointment when those expectations are not met [6, 17]. Parise et al., investigated how cooperation with a computer agent was affected by the agent's pictorial realism and human likeness. Participants played a game with a talking computer agent that resembled a person, a real dog, a cartoon dog, or with a confederate through a video link. They found that participants cooperated highly with the agent resembling a person and the confederate. Although participants loved the dog and dog cartoon agents, they cooperated significantly less with the dog agents [18]. Huang [8] conducted a study that manipulated the interactivity and expressiveness of agents. She found that users who encountered an emotionally expressive agent perceived higher levels of social presence of the agent and that interactivity of the agent was a strong predictor of learning. In addition, users who used interactive media perceived animated agents to be more credible and perceived the expressive agent as more sociable and likeable. However, using an interface agent may not always be beneficial. Walker [26] indicates that having a face in an interface takes more effort and attention from the user than a text display and may make the experience for the user worse rather than better. Virtual Humans The importance of using virtual humans in clinical or training applications is becoming increasingly apparent. Case studies have indicated that exposure to a virtual audience can be helpful in the treatment for fear of public speaking [1]. Slater, et al., examined the extent to which virtual humans could be used by actors and a director to rehearse for a live performance. The authors suggest that a performance level was reached in the virtual rehearsal which led to a successful live performance, one that could not have been achieved by only learning of lines or video conferencing [23]. Virtual humans have also been used by medical students to practice patient interviewing skills using natural methods of interaction with a high level of immersion [9]. There is also a virtual reality training tool in development for nursing students which will allow practice with verbally interviewing, observing, and examining patients [28]. Researchers have even applied social psychology principles to virtual human research. Slater, et al., conducted studies on the effects and social ramifications of having avatars in virtual environments [24]. They were able to elicit emotions such as embarrassment, irritation, and self-awareness in virtual meetings; and they found that the presence of avatars was important for social interaction, task performance, and presence [24]. Other studies have shown that a virtual audience induces social anxiety and that the degree of anxiety is related to the type of feedback the audience provides [19]. The utility of using immersive virtual environment technology, including virtual humans, Figure 1. Real and virtual speakers for social psychological research is also the subject of current research [2]. In a previous study, we investigated social interaction effects with human-virtual and human-human interactions. These effects refer to performance enhancement of a simple or well learned task, and performance impairment of a complex or novel task, when done in the presence of others. Participants performed either a learned or a novel task, alone, in the presence of a virtual human, or in the presence of a real human. We found that participants reacted to the virtual human similarly to the way they reacted to the real human. In particular, women performed worse on the novel task in the presence of a virtual human than alone [27]. EXPERIMENTAL STUDY The intent of this study was to use virtual characters to replicate previous experiments on persuasion [11, 25]. Whereas the previous studies focused on speech type, we examined the roles of gender and visual realism on the persuasiveness of a speaker. Participants listened to a message designed to change their attitude about university-wide comprehensive exams. The message was delivered by a male or female human (Jonathan and Amy), virtual human (Jack and Diana), or 1155

4 virtual character (Tom and Ginger). The speakers are presented in Figure 1. Even though the virtual characters used in this study were floating heads only, while the virtual human and real human speakers had a head and torso, we do not expect this difference to affect our results because recent research has shown that the presence or absence of torso had no effect on the participants perceptions of an avatar [17]. Building on previous studies comparing different levels of anthropomorphic agents and the literature comparing virtual humans to real people [4, 8, 10, 16, 17, 19, 18, 23, 27], we expect that virtual speakers will be as persuasive as human speakers. And based on the literature regarding the effects of gender on persuasion [3, 5], we expect gender effects to occur with our virtual speakers. We tested the following hypotheses: Hypothesis 1: Significant changes in attitude are expected in response to each of the speakers on the target topic. Hypothesis 2: The gender of the speaker will have an effect on persuasiveness and on the ratings of the perceptions of the argument, message, and speaker. Participants A total of 138 students (41 males, 97 females, mean age = 20.6, SD = 4.09) from the University of North Carolina at Charlotte participated in the study. Volunteers were recruited from the psychology department subject pool, and all received credit points towards their psychology class grade. Stimulus Materials The persuasive argument was a passage in favor of university-wide comprehensive exams. The argument was adapted from models of strong arguments provided by Petty and Cacioppo (1986) to include The University of North Carolina at Charlotte [20]. For the human speaker conditions, two graduate students (Jonathan and Amy) were video and audio recorded with a Panasonic NV GS70 video camera. For the virtual human and character conditions, we used Haptek Corporation s [7] interactive 3-D characters to create our virtual speakers, Jack, Diana, Tom, and Ginger (Figure 1). A Pentium IV 2.4 GHz Dell PC with an nvidia GeForce4 Ti 4200 graphics card served as the graphics generator for the virtual characters. The graphics were rendered with OpenGL and then screen captured to create videos of these conditions. Due to the limitations of our video screen capture device, the audio for the virtual speakers was captured in mono. The human speakers in this study (Jonathan and Amy) also served as the voices of our virtual speakers. Haptek s lipsynch software was used so that the audio matched the lip movements of the virtual characters. A Sony Vaio Pentium IV 2.0 GHz laptop was used to play the videos of all speakers. The videos were projected using a Sony VPL-CX5 data projector. Two speakers at the bottom of the projection screen were used to output the audio for all conditions. Dependent Variables Pre and Post Tests Attitudes about the four topics were measured using pre and post tests developed by Mullennix, et al., [11]. The tests consisted of 12 items that used a 7-point Likert-type scale (1 = disagree completely, 7 = agree completely). Three items measured attitudes relevant to the content of the persuasive message (comprehensive exams), and the remaining items were related to three control topics (animal rights, environmentalism and a raise in tuition). These topics were included to measure whether listening to the persuasive argument on comprehensive exams would lead to a significant change in attitude on topics unrelated to the persuasive message. In fact, Mullennix et al., found that attitudes on the campus-related topic of a raise in tuition were affected by the persuasive appeal of comprehensive exams [11]. Pre and post test scores were compared and any change in attitude with regards to the topic of comprehensive exams was used to determine the level of persuasion. Perceptions of the Argument, Message, and Speaker The participants' perceptions of the persuasive argument, message and speakers were assessed through an eighteen item questionnaire comprised of semantic differential items adapted from Mullennix et al., [11]. Items were selected based on their relevance to the questions under investigation. Items related to perception of the argument were measured on a 9-point numerical rating scale while those for perception of the message and speaker used a 7-point scale. Items for each are as follows: perception of the argument (bad-good; foolish-wise; negative-positive; beneficialharmful; effective-ineffective; convincing-unconvincing); perception of the message (stimulating-boring, vaguespecific, unsupported-supported, complex-simple, convincing-unconvincing, uninteresting-interesting); and perceptions of the speaker (incompetent-competent, honestdishonest, unassertive-assertive, uninformed-informed, untrustworthy-trustworthy, timid-bold). Principle components analysis was used on the item ratings of the argument, speaker, and message to determine how to combine the items into factor scores. Items with factor loadings above 0.5 were retained. Factor scores were produced by summing the item weights. The factor analysis of items related to argument yielded only one factor. All 6 of the items loaded heavily on that factor. The reliability of that factor when all the items were combined was high (Cronbach's alpha = 0.90). 1156

5 measured on their attitudes regarding four topics (comprehensive exam, and three control topics) before and after hearing the persuasive argument. Participants were run in small groups (1 to 3 per group). The speaker s image was projected onto a wall directly in front of the participants (Figure 2). Two audio speakers placed on floor below the projected image were used to output the audio. Participants first filled out a demographics questionnaire and then the pre-test. They were then presented with a persuasive message about the benefits of university-wide comprehensive exams. After hearing the message, participants filled out the post-test as well as questions on perceptions of the argument, the message, and the speaker. Participants were then debriefed and thanked for their participation. Figure 2. Experimental setup The factor analysis of items related to message yielded two factors: Interesting, which accounted for 39% of the variance, (included Stimulating, Specific, Supported, Convincing, and Interesting) and Conservative which explains 19% of the variance. Cronbach's alpha for the first factor is Finally, the factor analysis of items related to speaker yielded two factors: Trustworthy (which combines Competent, Informed, and Trustworthy dimensions) and Bold (which combines Bold and Assertive). The first factor explains 44% of the variance and has a Cronbach's alpha reliability coefficient of The second factor explains 19% of the variance and has a Cronbach's alpha reliability coefficient of Design and Procedure Male and female participants were randomly assigned to one of six experimental conditions in which speaker gender (male/female) and speaker realism (human, virtual human and virtual character) are combined. Each participant was RESULTS Mean test scores were computed across participants for each of the message topics. These means were treated with a 2 x 3 x 2 ANOVA to test for the between subject effects of speaker s gender, and speaker realism, and the within subject effect of pre and post testing. For the subjective ratings data, sums of the factor loadings were computed and analyzed with a 2 x 3 ANOVA to test for the between subject effects of speaker gender and speaker realism. A second ANOVA was conducted on the pre and post difference scores and the subjective ratings to explore interaction effects between the gender of listener and the gender of the speaker. For post hoc analysis, we used the Tukey s HSD (Honestly Significant Difference) test. Pre and Post Tests Table 1 shows the pre and post differences obtained in attitudes regarding each of the four topics that were tested. Significant changes in attitude occurred in response to each of the speakers on the target topic of comprehensive exams, F(1, 132) = 89.46, p < 0.01, and tuition increase F(1, 132) = , p < For the other topics, the pre post Comprehensive Tuition Animal Rights Environment Pre Post Diff Pre Post Diff Pre Post Diff Pre Post Diff Jonathan Amy Jack Diana Tom Ginger Total Table 1. Pre and post differences in attitudes on each topic as a function of speaker. Changes in attitude on the comprehensive exam topic and the campus related topic of tuition increase were significant for all speakers, p <

6 Figure 3. Level of persuasion by topic and speaker differences were in the opposite direction. The pattern of data can be seen in Figure 3 which shows the mean differences on pre and post tests by topic and speaker. The fact that a significant change in opinion was also found with the control topic of tuition increase is not surprising since several participants stated during the debriefing that they thought that the tuition increase would pay for the comprehensive exam. Also, in a previous experiment using the same materials, Mullennix, et al., also found a positive change in attitude on the topic of a tuition increase [11]. However, a planned comparison on the mean differences scores showed that the attitude change associated with the comprehensive exam topic was significantly greater than the attitude change associated with the three control topics, t paired (137) = 8.09, p < To examine the effect of speaker gender on persuasiveness (Hypothesis 2), we compared the pre and post differences for male and female speakers on the attitude measure for the comprehensive exam topic. Inconsistent with Hypothesis 2, the gender of the speaker did not have an effect on the speaker s persuasiveness, F < 1. To examine the effect of speaker realism on persuasiveness, we compared the pre and post differences on the attitude measure for the comprehensive exam topic. However, there was no significant effect of speaker realism on persuasion, F(2, 132) = 1.37, p = Virtual speakers were as effective as real speakers, and virtual character speakers were as effective as virtual human speakers in persuading participants on the benefits of comprehensive exams. Also, speaker realism was not found to interact with speaker gender, F < 1. The difference scores on the target topic presented in Table 1 were analyzed with a 2 x 2 between subjects analysis to examine interaction effects between listener and speaker gender. Figure 4 shows the significant cross gender effect that was found, F(1, 134) = 5.78, p < Male participants were more persuaded by female speakers than male speakers, and female participants more persuaded by male speakers than female speakers. Although the literature states that women are more susceptible to persuasion than men [5], we did not get this result. The difference in the level of persuasion for male (M = 3.34, N = 41, SD = 5.11) and female (M = 3.04, N = 97, SD = 3.25) listeners was not significant, F < 1. However, 1158

7 argument, there was no significant effect of realism on the perceptions of argument, F < 1 Finally, a speaker gender x listener gender analysis of variance was used to test for gender interactions on the ratings for the perceptions of the argument. There was no interaction effect of listener gender and speaker gender on the ratings for the perceptions of the argument, F < 1. Perceptions of the Message To examine the effect of speaker gender on the ratings of the perceptions of the message (Hypothesis 2), we compared the ratings of the female speakers with the ratings of the male speakers on the two dimensions of the perceptions of the message. There were no significant effects of gender on the two dimensions of the perceptions of message, Fs < 1. To examine the effect of speaker realism on the ratings of the perceptions of the message, we compared the ratings of the human speakers with the ratings of the virtual speakers on the two dimensions of the perceptions of the message. There were no significant effects of realism on the two dimensions of the perceptions of message Fs < 1. Figure 4. Cross gender interaction on attitude change for persuasive topic we had far more female than male participants and the failure to balance this variable could have biased the results. Perceptions of the Argument Table 2 shows the factor scores produced from the rating data that measured perceptions of the argument, message, and speaker. The data are averaged across participants. To examine the effect of speaker gender (Hypothesis 2), we compared the male and female ratings on the perceptions of the argument and there was no significant effect of gender, F < 1. When we compared the ratings of the human speakers with the ratings of the virtual speakers on the perceptions of the Next, a speaker gender (2) x listener gender (2) analysis of variance was used to test for gender interactions on the ratings for the perceptions of the message. However, there was no interaction effect of listener gender and speaker gender on the Conservative (F(1, 134) = 1.28, p = 0.26) or the Interesting (F < 1) dimensions of the perceptions of the message. Perceptions of the Speaker To examine the effect of speaker gender on the ratings of the perceptions of the speaker (Hypothesis 2), we compared the ratings of the female speakers with the ratings of the male speakers on the two dimensions of the perceptions of the speaker. However, there were no significant effects of gender on the two dimensions of the perceptions of speaker, Fs < 1. Measure Amy Diana Jonathan Jack Ginger Tom Perceptions of the argument Effective (combines 6 items) Perceptions of the message Conservative- (1 item) Interesting - (combines 5 items) Perceptions of the speaker Trustworthy (combines 4 items) Bold (combines 2 items) Table 2. Factor loadings for the rating data displayed as a function of speaker. Perception of the argument was measured with a 9-point rating scale, while perception of the message and speaker used a 7-point rating scale. 1159

8 To examine the effect of speaker realism on the ratings of the perceptions of the message, we compared the ratings of the human speakers with the ratings of the virtual speakers on the two dimensions of the perceptions of the speaker. There was no effect of realism on the Trustworthy dimension, (F < 1), however virtual speakers were rated significantly more Bold (F(2, 132) = 7.91, p < 0.01) than human speakers. This was a surprising result since it is unexpected that participants rated virtual speakers more favorably than the human speakers! A post hoc (Tukey s HSD) test revealed that virtual characters (M = 5.00, N = 47, SD = 1.10) were rated significantly more Bold than real humans (M = 4.08, N = 44, SD = 1.30), p < Virtual humans (M = 4.84, N = 47, SD = 1.07) were also rated significantly more Bold than real humans, p < The difference between the virtual characters and virtual humans was not significant. Finally, a speaker gender (2) x listener gender (2) analysis of variance was used to test for gender interactions on the ratings for the perceptions of the speaker. There were no interaction effects of listener gender and speaker gender on either of the dimensions of the perceptions of the speaker, Fs < 1. DISCUSSION The focus of this study was on the effects of speaker gender and realism on persuasiveness. Realism of the characters referred to the visual representation not the character s voice. The same male human voice was used for all male speakers and the same female human voice was used for all the female speakers; previous work has focused on the effect of speech type on persuasion [11, 25]. This study showed that college students found the virtual characters used in this study as persuasive as real people. The fact that the degree of persuasion did not interact with real or virtual speaker conditions suggests that virtual characters with human voices can be just as effective at changing attitudes about topics of interest as real people. Our main finding was that the visual realism of the speakers did not have an effect on the degree of persuasion. The virtual speakers used in this study were as effective in persuading participants on the topic of comprehensive exams as real speakers. These results align with the findings of previous research that has also shown that people tend to respond to virtual humans similarly to the way they respond to real people [19, 24, 27]. Our results also revealed gender interactions that occurred in a similar pattern across all speaker conditions, real and virtual. Male participants were more persuaded by the female speakers than the male speakers, and female participants were more persuaded by the male speakers than the female speakers. This significant interaction between the gender of the speakers and gender of the participants replicates gender stereotypes that are common in social interaction studies [3, 5] and suggests that some of the same cross gender effects are occurring with virtual characters. Another interesting finding was that participants rated the virtual speakers as more Bold than real speakers. It was unexpected that participants would rate the virtual speakers more favorably than the real speakers. This may be due to participants possibly having lower expectations for a virtual character, such as a cat, than for a real person. Our results have implications for future designers of interfaces that involve persuasion (from e-commerce web sites to medical advice software). Designers of persuasive interfaces that involve a virtual character should be concerned with the gender of the character. The fact that participants were more influenced by the opposite gender indicates that customization of a virtual character according to the user s preference will increase the persuasive appeal of that character. Also, the fact that participants rated the virtual speakers used in this study more favorably than human speakers suggests that there may be an advantage to using certain virtual characters over real humans in persuasive interfaces. Persuasive interfaces should take advantage of the flexibility of virtual characters. With virtual characters, the user can easily customize the gender, age, race, physical appearance, attire, or even species of the character to match his or her preferences. LIMITATIONS OF THIS WORK The results of this study are limited to the virtual characters employed in our experiment and may not generalize to other types of virtual characters. Further research is needed that examines the extent to which our findings can generalize to a broader variety of virtual characters. One limitation of this study was the appearance of the virtual characters. The male virtual character had an 'Ogrelike' appearance, while the female virtual character had a more friendly 'Cat-like' appearance. This mismatch in appearance for the virtual characters may have influenced our results. Further research is needed to examine the effect of having matched male and female 'Ogre-like' characters and/or male and female 'Cat-like' characters. Another drawback was the uneven number of male and female participants who were available for the study. More male participants are needed to fully examine the gender effects. Finally, to achieve more generalizable findings, this study should be replicated with a sample that includes more diverse groups of people, not just college students. FUTURE WORK In this study, we used pre-recorded human voices, rather than text-to-speech (TTS), for our virtual speakers. This was because we wanted to isolate the effects of speech type from the effects of gender and visual realism. Previous 1160

9 research has focused on speech quality, TTS versus human voice, and how it affects the degree of persuasion [11, 25]. Future studies should combine these efforts and examine how speech quality interacts with visual realism and gender in the study of persuasion. In future work, we would also like to run the same experiment with a balanced number of male and female participants in order to more fully examine the effects of gender on attitude change. ACKNOWLEDGMENTS The authors would like to thank Amy Ulinski and Jonathan Jackson for providing both the audio for the virtual speakers and the video and audio for the real speakers. The authors would also like to thank all the participants who took part in this study. REFERENCES 1. Anderson, P., Rothbaum, B.O., and Hodges, L. F. Virtual reality exposure in the treatment of social anxiety. Cognitive and Behavioral Practice, 10, (2003), Blascovich, J., Loomis, J., Beall, A., Swinth, K., Hoyt, C., and Bailenson, J. Immersive virtual environment technology: Not just another research tool for social psychology. Psychological Inquiry, 13, (2002), Carli, L.L. Gender, Language, and Influence. Journal of Personality and Social Psychology, 59, (1990), Choi, Y. K., Miracle, G. E., and Biocca, F. The effects of anthropomorphic agents on advertising effectiveness and the mediating role of presence. Journal of Interactive Advertising, 2, 1 (2001), Online. 5. Eagly, A. H. Sex Differences in Influenceability. Psychological Bulletin, 85, (1978), Garau, M., Slater, M., Vinayagamoorthy, V., Brogny, A., Steed, A., and Sasse, M. A. The impact of avatar realism and eye gaze control on perceived quality of communication in a shared immersive virtual environment. In Proc. CHI ACM Press (2003). 7. Haptek Corporation Huang, H.-Y. The persuasion, memory and social presence effects of believable agents in human-agent communication. In Proc.International Cognitive Technology Conference Johnsen, K., Dickerson, R., Raij, A., Lok, B., Jackson J., Shin, M., Hernandez, J., Stevens, A., and Lind, D. S. Experiences in Using Immersive Virtual Characters to Educate Medical Communication Skills. In Proc. IEEE Virtual Reality Koda, T., and Maes, P. Agents with faces: The effect of personification. In Proc. IEEE International Workshop on Robot and Human Communication 1996, 189-l Mullennix, J.W., Stern, S.E., Wilson, S.J., and Dyson, C. Social perception of male and female computer synthesized speech. Computers in Human Behavior, 19, (2003), Nass, C., and Lee, K. M. Does computer-generated speech manifest personality? An experimental test of similarity-attraction. Proc. CHI 2000, ACM Press (2000), Nass, C., and Moon, Y. Machines and mindlessness: Social responses to computers. Journal of Social Issues, 56, (2000), Nass, C., Moon, Y., and Green, N. Are Machines Gender Neutral? Gender-Stereotypic Responses to Computers with Voices. Journal of Applied Social Psychology, 27, (1997), Nass, C., Steuer, J. S., and Tauber, E. Computers are social actors. Proc. CHI 1994, ACM Press (1994), Nowak, K. L., and Biocca, F. The effect of the agency and anthropomorphism of users' sense of telepresence, copresence, and social presence in virtual environments. Presence: Teleoperators and Virtual Environments, 12, 5 (2002), Nowak, K. L., and Rauh, C. The influence of the avatar on online perceptions of anthropomorphism, androgyny, credibility, homophily, and attraction. Journal of Computer-Mediated Communication, 11, 1 (2005), article Parise, S., Kiesler, S., Sproull L., and Waters, K. My Partner is a Real Dog: Cooperation with Social Agents. In Proc. CSCW 1996, ACM Press (1996), Pertaub, D. P., Slater, M., and Barker, C. An experiment on public speaking anxiety in response to three different types of virtual audience. Presence: Teleoperators and Virtual Environments, 11, (2002), Petty, R. E., and Cacioppo, J. T. Communication and Persuasion, Springer Verlag, New York, USA, Priester, J. R. and Petty, R. E. Source attributions and persuasion: Perceived honesty as a determinant of message scrutiny. Personality and Social Psychology Bulletin, 21, (1995), Reeves, B., and Nass, C. The Media Equation: How People Treat Computers, Television, and New Media like Real People and Places. Cambridge University Press, New York, USA, Slater, M., Howell, J., Steed, A., Pertaub, D. P., Garau, M., and Springel, S. Acting in Virtual Reality, Proc. Collaborative Virtual Environments 2000, ACM Press (2000), Slater, M. and Usoh, M. Body Centered Interaction in Immersive Virtual Environments, in Artificial Life and Virtual Reality, N. Magnenat Thalmann and D. Thalmann, Eds, John Wiley and Sons, (1994),

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