Virtual research assistants: Replacing human interviewers by automated avatars in virtual worlds

We conducted an experiment to evaluate the use of embodied survey bots (i.e., software-controlled avatars) as a novel method for automated data collection in 3D virtual worlds. A bot and a human-controlled avatar carried out a survey interview within the virtual world, Second Life, asking participants about their religion. In addition to interviewer agency (bot vs. human), we tested participants’ virtual age, that is, the time passed since the person behind the avatar joined Second Life, as a predictor for response rate and quality. The human interviewer achieved a higher response rate than the bot. Participants with younger avatars were more willing to disclose information about their real life than those with older avatars. Surprisingly, the human interviewer received more negative responses than the bot. Affective reactions of older avatars were also more negative than those of younger avatars. The findings provide support for the utility of bots as virtual research assistants but raise ethical questions that need to be considered carefully.     

Avatars Versus Agents: A Meta-Analysis Quantifying the Effect of Agency on Social Influence

Existing research has investigated whether virtual representations perceived to be controlled by humans (i.e., avatars) or those perceived to be controlled by computer algorithms (i.e., agents) are more influential. A meta-analysis (N = 32) examined the model of social influence in virtual environments (Blascovich, 2002) and investigated whether agents and avatars in virtual environments elicit different levels of social influence. Results indicated that perceived avatars produced stronger responses than perceived agents. Level of immersion (desktop vs. fully immersive), dependent variable type (subjective vs. objective), task type (competitive vs. cooperative vs. neutral), and actual control of the representation (human vs. computer) were examined as moderators. An interaction effect revealed that studies conducted on a desktop that used objective measures showed a stronger effect for agency than those that were conducted on a desktop but used subjective measures. Competitive and cooperative tasks showed greater agency effects than neutral tasks. Studies in which both conditions were actually human controlled showed greater agency effects than studies in which both conditions were actually computer controlled. We discuss theoretical and design implications for human–computer interaction and computer-mediated communication.     

The embodiment of sexualized virtual selves: The Proteus effect and experiences of self-objectification via avatars

Research has indicated that many video games and virtual worlds are populated by unrealistic, hypersexualized representations of women, but the effects of embodying these representations remains understudied. The Proteus effect proposed by Yee and Bailenson (2007) suggests that embodiment may lead to shifts in self-perception both online and offline based on the avatar’s features or behaviors. A 2 × 2 experiment, the first of its kind, examined how self-perception and attitudes changed after women (N = 86) entered a fully immersive virtual environment and embodied sexualized or nonsexualized avatars which featured either the participant’s face or the face of an unknown other. Findings supported the Proteus effect. Participants who wore sexualized avatars internalized the avatar’s appearance and self-objectified, reporting more body-related thoughts than those wearing nonsexualized avatars. Participants who saw their own faces, particularly on sexualized avatars, expressed more rape myth acceptance than those in other conditions. Implications for both online and offline consequences of using sexualized avatars are discussed.     

“It doesn’t matter what you are!” Explaining social effects of agents and avatars

Empirical studies have repeatedly shown that autonomous artificial entities, so-called embodied conversational agents, elicit social behavior on the part of the human interlocutor. Various theoretical approaches have tried to explain this phenomenon: According to the Threshold Model of Social Influence (Blascovich et al., 2002), the social influence of real persons who are represented by avatars will always be high, whereas the influence of an artificial entity depends on the realism of its behavior. Conversely, the Ethopoeia concept (Nass & Moon, 2000) predicts that automatic social reactions are triggered by situations as soon as they include social cues. The presented study evaluates whether participants´ belief in interacting with either an avatar (a virtual representation of a human) or an agent (autonomous virtual person) lead to different social effects. We used a 2 × 2 design with two levels of agency (agent or avatar) and two levels of behavioral realism (showing feedback behavior versus showing no behavior). We found that the belief of interacting with either an avatar or an agent barely resulted in differences with regard to the evaluation of the virtual character or behavioral reactions, whereas higher behavioral realism affected both. It is discussed to what extent the results thus support the Ethopoeia concept.     

From Embodied Agents or Their Environments Reasoning About the Body, to Virtual Models of the Human Body: A Quick Overview

This article provides an overview of such embodied agents that reason about the body, e.g., self-reconfiguring robots, and of research into recognizing a body part as belonging to one’s own body, on the part of robotic agents (vs. animals). More sketchily, we also consider such animated avatars whose movements imitate human body movements, and virtual models of the human body.     

How do varied populations interact with embodied conversational agents? Findings from inner-city adolescents and prisoners

Two studies were conducted to identify individual characteristics that predict behavioral responses to violence prevention interventions. These studies used embodied conversational agents (ECAs) to create hypothetical social situations (called virtual vignettes) to assess interpersonal competency skills. One study was of male inner-city African–American adolescents, and the second was of male prisoners in a state correctional system. In pre- and post-intervention sessions, participants interacted with an ECA that tried to entice them into making risky decisions. The virtual vignette sessions tested participants’ negotiation and conflict resolution skills. Results showed differing tendencies for participants to be engaged by the virtual vignettes. The vignettes were sufficiently realistic to elicit differences in behavior among the adolescents, but generally not for the prisoners. Prior acceptance, accessibility, and usability data suggest that most users readily accept ECAs as valid conversational partners. The evidence presented here suggests that the technology – or the setting in which the technology is used – is not by itself sufficient to actively engage users. The usefulness of virtual vignettes to adequately predict future behavior may be at least partially influenced by participant characteristics.     

Visualizing ideal self vs. actual self through avatars: Impact on preventive health outcomes

The self-discrepancy between one’s actual self and one’s ideal self, which is associated with negative emotional states (e.g., depression) or unhealthy lifestyles (e.g., eating disorders), is mostly caused and intensified by exposure to unrealistic images of others (e.g., celebrities or magazine models). Drawing from regulatory focus theory, the current study examines whether creating self-resembling avatars, especially those that resemble our ideal selves, could counteract this negative effect of self-discrepancy. The results of a between-subject experiment (N = 95) indicated that user-created self-reflecting avatars made salient different mental images of their bodies based on whether they customized their avatars to look like their actual or ideal selves, and consequently influenced their perceptions toward their physical body through two different self-regulatory systems (i.e., promotion-focused and prevention-focused), with consequences for health outcomes. Theoretical and practical implications are discussed.     

Exploring the social competence of students with autism spectrum conditions in a collaborative virtual learning environment – The pilot study

Social reciprocity deficits are a core feature of the autism spectrum conditions (ASCs). Many individual with ASCs have difficulty with social interaction due to a frequent lack of social competence. This study focuses on using a virtual learning environment to help the deficiencies of social competence for people with ASCs, and to increase their social interaction. Specifically, it primitively explores social competence in collaborative virtual learning environment (CVLE) systems, and behavioral performance in social and cognitive interactions. Thus, this CVLE-social interaction system involves a 3D expressive avatar, an animated social situation, and verbal as well as text-communication. A preliminary empirical study involved CVLE-social interaction systems. Three participants who had been diagnosed with ASCs were conducted using a multiple baseline research for evidence of improved social competence through usage of the system. The experimental study consisted of 17 days; and the results showed that using the CVLE-social interaction system had significant positive effects on participants’ performance, both within the CVLE-social interaction system and in terms of reciprocal social interaction learning.     

Investigating recognition-based performance in an open content community: A social capital perspective

As the open source movement grows, it becomes important to understand the dynamics that affect the motivation of participants who contribute their time freely to such projects. One important motivation that has been identified is the desire for formal recognition in the open source community. We investigated the impact of social capital in participants’ social networks on their recognition-based performance; i.e., the formal status they are accorded in the community. We used a sample of 465 active participants in the Wikipedia open content encyclopedia community to investigate the effects of two types of social capital and found that network closure, measured by direct and indirect ties, had a significant positive effect on increasing participants’ recognition-based performance. Structural holes had mixed effects on participants’ status, but were generally a source of social capital.     

“I want to be different from others in cyberspace” The role of visual similarity in virtual group identity

The present study investigated the impact of the visual similarity shared among virtual group members on group identity and conformity. In achieving this goal, the current study distinguished the similarity coming from being in the same experimental group (i.e., transient group membership) and the similarity coming from the same social group membership (i.e., lasting group membership), in response to the critique that these two group memberships have not been set apart in previous computer-mediated group research. The current study also attended to the fact that previous research on computer-mediated groups restricted personality traits that might have affected group identity formation and conformity in virtual groups. In response to this constraint, the present study included participants’ needs to be different from others (NFU) and needs for inclusion (ISC) to a hypothesized path model that was founded on the SIDE model. Furthermore, the author examined whether the same hypothesized path model could uphold across the differentiated levels of similarity shared among group members.     

Nested Beliefs, Goals, Duties, and Agents Reasoning About their Own or Each Other’s Body in the TIMUR Model: A Formalism for the Narrative of Tamerlane and the Three Painters

This article develops two threads. The first thread argues that the narrative dimension of social interaction is important to societies of embodied agents: not only to animated avatars in virtual environments (for which, behaviour specification languages are useful, simplifying the distinct task of feeding a narrative into the system), but also, arguably, in societies of robots, because categories of patterns of action can arguably be usefully captured by modifications of levels of abstraction originally developed by structuralism for folktale studies. This first thread does not depend, for its validity, on the second thread. The other thread of this paper is to analyze a story of interaction among characters with different social positioning, such that reasoning on the body of one of them is central. We develop the analysis by resorting to episodic formulae, a method of representation developed by the present author and often applied during the last several years.     

Testing a model of sense of virtual community

A distinguishing feature of virtual communities is their sense of community, i.e., their participants’ feelings of membership, identity, influence, and attachment with each other. This study tests a model in which members’ perceptions of the group’s norms mediate the relationships between supporting each other and identifying each other with the members’ sense of virtual community. Two studies were conducted providing partial support for the model. The results show that the perception of norms mediate the relationship between SOVC and (a) observing and publicly exchanging support, (b) perceiving that others know one’s identity, and (c) using technical features to learn and create identity. Theoretical and practical implications are discussed.     

Applying social bookmarking to collective information searching (CIS): An analysis of behavioral pattern and peer interaction for co-exploring quality online resources

With the advancement of Web 2.0 applications, this study aims to advocate that social bookmarking (SB) applications could support mutual exchange of finding information in a manner of collective information searching (CIS). A social bookmarking system, namely ‘WeShare,’ was developed, and conducted with 127 junior high school students for performing the given assignment in this study. The participants’ activities of collecting and reviewing relevant information were traced by log data for later analysis. To initially unveil the participants’ behaviors in the use of social bookmarking for co-exploring the Internet resources, this study proposed some quantitative indicators to represent students’ personal contributions (‘Bookmarks from the Internet,’ ‘Bookmarks from WeShare,’ ‘Annotations on personal bookmarks,’ ‘Comments on others’ bookmarks’) and peer feedback (‘The number of bookmarks collected by peers,’ ‘The number of bookmarks commented on by peers,’ ‘The number of comments from peers’). By the method of cluster analysis, some behavioral patterns regarding how participants collectively search the Internet by use of WeShare were identified. Furthermore, the findings suggest that personal contributions to citing and commenting on peers’ bookmarks are important to the advancement of collective information searching activities for finding quality information on the Internet.     

I became an attractive person in the virtual world: Users’ identification with virtual communities and avatars

A number of studies have examined virtual worlds, which can facilitate knowledge sharing, education, and enjoyment, among others. However, no study has provided an insightful research model for evaluating virtual worlds. This study suggests that users’ identification with virtual communities and avatars plays a critical role in the construction of attractive virtual worlds. The proposed model measures the level of the user’s identification with virtual communities, through which the user builds his or her trust in other community members. In addition, the study suggests that users’ identification with avatars is an important element of their satisfaction with virtual worlds. The results indicate that users’ identification with virtual communities as well as avatars can enhance their efficacy and trust and thus facilitate their sustained use of virtual services. The results have important theoretical and practical implications.     

Inferences About Avatars: Sexism,Appropriateness, Anthropomorphism,and the Objectification of Female Virtual Representations

This study integrated the computers as social actors (CASA) framework with objectification theory to predict that traits, such as sexism, influence perceptions of virtual representations as well as attributions of the source and message. Participants (N = 397) received a message about dating or job interviews presented by a virtual woman in either context‐appropriate or context‐inappropriate dress. Causal modeling techniques revealed that participants higher on sexism rated the representations as less human (i.e., less anthropomorphic) and less credible. Further, perceived appropriateness of clothing and anthropomorphism influenced perceptions of source trust and message clarity. Implications for understanding the role of trait variables such as sexism on perceptions of virtual representations are discussed.     

Theory and measurement of generalized problematic Internet use: A two-step approach

This study tested an updated cognitive-behavioral model of generalized problematic Internet use and reports results of a confirmatory analysis of the Generalized Problematic Internet Use Scale 2 (GPIUS2). Overall, the results indicated that a preference for online social interaction and use of the Internet for mood regulation, predict deficient self-regulation of Internet use (i.e., compulsive Internet use and a cognitive preoccupation with the Internet). In turn, deficient self-regulation was a significant predictor of the extent to which one’s Internet use led to negative outcomes. Results indicated the model fit the data well and variables in the model accounted for 27% of the variance in mood regulation scores, 65% of variance in participants’ deficient self-regulation scores, and 61% of variance in the negative outcome scores.     

Humanoid Audio–Visual Avatar With Emotive Text-to-Speech Synthesis

Emotive audio–visual avatars are virtual computer agents which have the potential of improving the quality of human-machine interaction and human-human communication significantly. However, the understanding of human communication has not yet advanced to the point where it is possible to make realistic avatars that demonstrate interactions with natural- sounding emotive speech and realistic-looking emotional facial expressions. In this paper, We propose the various technical approaches of a novel multimodal framework leading to a text-driven emotive audio–visual avatar. Our primary work is focused on emotive speech synthesis, realistic emotional facial expression animation, and the co-articulation between speech gestures (i.e., lip movements) and facial expressions. A general framework of emotive text-to-speech (TTS) synthesis using a diphone synthesizer is designed and integrated into a generic 3-D avatar face model. Under the guidance of this framework, we therefore developed a realistic 3-D avatar prototype. A rule-based emotive TTS synthesis system module based on the Festival-MBROLA architecture has been designed to demonstrate the effectiveness of the framework design. Subjective listening experiments were carried out to evaluate the expressiveness of the synthetic talking avatar.      

Deploying embodied AI into virtual worlds

Unlike computer games where Non-Player-Character avatars are common, in most virtual worlds they are the exception. Deploying an embodied AI into a virtual world offers a unique opportunity to evaluate embodied AIs, and to develop them within an environment where human and computer are on almost equal terms. This paper presents an architecture being used for the deployment of chatbot driven avatars within the Second Life virtual world, looks at the challenges of deploying an AI within such a virtual world, the possible implications for the Turing Test, and identifies research directions for the future.     

Corruptible social agents

Agent‐based virtual simulations of social systems susceptible to corruption (e.g., police agencies) require agents capable of exhibiting corruptible behaviors to achieve realistic simulations and enable the analysis of corruption as a social problem. This paper proposes a formal belief‐desire‐intention framework supported by the functional event calculus and fuzzy logic for modeling corruption based on the integrity level of social agents and the influence of corrupters on them. Corruptible social agents are endowed with beliefs, desires, intentions, and corrupt‐prone plans to achieve their desires. This paper also proposes a fuzzy logic system to define the level of impact of corruption‐related events on the degree of belief in the truth of anti‐corruption factors (e.g., the integrity of the leader of an organization). Moreover, an agent‐based model of corruption supported by the proposed belief‐desire‐intention framework and the fuzzy logic system was devised and implemented. Results obtained from agent‐based simulations are consistent with actual macro‐level patterns of corruption reported in the literature. The simulation results show that (i) the bribery rate increases as more external entities attempt to bribe agents and (ii) the more anti‐corruption factors agents believe to be true, the less prone to perpetrate acts of corruption. Copyright © 2014 John Wiley & Sons, Ltd.