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

Transcription

1 Avatars Versus Agents: A Meta-Analysis Quantifying the Effect of Agency on Social Influence Jesse Fox, Sun Joo (Grace) Ahn, Joris H. Janssen, Leo Yeykelis, Kathryn Y. Segovia & Jeremy N. Bailenson Presented by: Pantea Habibi

2 Outline Overview Research Design Meta-Analysis Results Implications Critique & Discussion 2

3 1 Overview 3

4 Overview Virtual representations of people in computer-mediated interactions Avatars Agents Hybrids Ability to behave in a human-like manner unique capabilities to influence users modify users attitudes and behaviors 4

5 Overview Social influence social norms conformity compliance Identification Social presence processes Identification social categorization perceive the representation 5

6 Overview I have a feeling that there is another dimension to this in that whether it matters would depend on the specificity of the task. For some tasks, it may matter and some others it might not. For some types of tasks, the exact identity might matter and for others, a less specific variation like gender might matter. [Harish] Social influence social norms conformity compliance Identification social presence processes Identification social categorization. perceive the representation 6

7 2 Research Design 7

8 Research purpose Virtual representations education, health, marketing, and other persuasive contexts important to identify the differences Determine whether perceived agency of a virtual representation affected social influence 8

9 Variables of Interest Perceived Control To enrich the analyses and application of the findings, relevant moderators included: Level of Immersion Immersive/Desktop Type of Measure Objective(behavioral)/Subjective(self-reported) DV Task Type Competitive/Cooperative/Neutral Actual Control Time 9

10 Variables of Interest I like how they could dissociate the actual content of the papers and just talk about high level goals of research they wanted to achieve. However, would the context / content affect the meta-analysis? (Comparatively the second paper, explained thoroughly each papers context and how it blended or did not with the other). [Aditi] Perceived Control To enrich the analyses and application of the findings, relevant moderators included: Level of Immersion Immersive/Desktop Type of Measure Objective(behavioral)/Subjective(self-reported) DV Task Type Competitive/Cooperative/Neutral Actual Control Time 10

11 Research Question Will agency effects on social influence vary between objective variables and subjective variables? Will actual control moderate the effect of perceived control on social influence? 11

12 Hypothesis Avatars will yield greater influence than agents. Studies conducted in immersive virtual environments will demonstrate smaller differences in the effects of agency than studies conducted in desktop environments. Competitive tasks will show the greatest differences in agency, followed by cooperative tasks, and neutral tasks will show the smallest differences in agency. 12

13 3 Meta-Analysis 13

14 Study Selection Bibliographic indices relating Virtual reality, communication, psychology, video gaming Databases: ScienceDirect, Google Scholar, etc. Search terms: Virtual representation, avatars, etc. Once a paper identified: References / reverse search Advertised on relevant listservs and contacted researchers Measured social influence 119 studies 14

15 I like the idea of contacting other researchers to get relevant work. I think that is also a good way to find more relevant papers. [Nina] Study Selection Bibliographic indices relating Virtual reality, communication, psychology, video gaming Databases: ScienceDirect, Google Scholar, etc. Search terms: Virtual representation, avatars, etc. Once a paper identified: References / reverse search Advertised on relevant listservs and contacted researchers Measured social influence 119 studies 15

16 Study Criteria DVs - quantitative measures of social influence presence or affect ratings, physiological measures, or interpersonal distance Have a visual representation Explicitly manipulate agency 36 studies 16

17 Final Round of Selection Minimally required statistics: means, standard deviations, and sample sizes per condition t values F values with degrees of freedom r values Cohen s d values 32 studies 17

18 Final Round of Selection I also like how they were able to get sample sizes and needed statistics by contacting authors. But, for the one study that they couldn't get enough information, why didn't they just exclude the study instead of assuming values? [Nina] Minimally required statistics: means, standard deviations, and sample sizes per condition t values F values with degrees of freedom r values Cohen s d values 32 studies The only case for which we were not able to obtain information was the Eastin and Griffiths (2006) studies, for which we assumed equal sample sizes across conditions. I agree with Nina for that one study that assumed the sample sizes but I am not very critical of that assumption as there is a clear selection criterion for the groups (8 and 5 grades), I might be wrong but I arrived at the reasoning based on papers where the American core syllabus for mid and high schoolers was being designed and had a similar assumption. [Sourabh] 18

19 Data Average sample size within each study: 71 Desktop: 21, immersive VE: 11 Tasks: Gaming: 16 7 Human, 9 Computer Non-gaming: Computers, 1 Human Type of tasks: Cooperative: 4 Competitive: 11 Cooperative and Competitive: 1 19

20 Effect Size Calculations Datasheet Studies DVs Measures (objective/subjective) Statistics + number of participants For each DV, calculated effect sizes r value t value means, standard deviations, and the number of cases in each condition 20

21 Effect Size Calculations Missing r value: Coded two values for r: coded r as zero avoids inflated results due to publication bias of significant effects maximum non-significant effect size based on the sample size Sign of r signifies the direction of the effect Positive: avatar condition yielded stronger responses on the DV than the agent condition 21

22 Effect Size Calculations Surveyed studies reported more than one DV of social influence conducted an analysis with DV as the unit of analysis conducted analyses using study as the unit of analysis 22

23 Data Sheet Sample 23

24 Statistical Analyses Calculated r values - weighted by sample size weighted r values were transformed to Fisher s Z values After aggregation, the averaged Fisher s Z values were transformed back to r values Grand mean and variance of r was calculated first source of variance around the mean r sampling error variance?? still unexplained variance left? moderator variables Assessed the n-r correlation 24

25 Statistical Analyses I did not clearly understand how they calculated the effect sizes they have brief discussion about filling in missing values and the n-r calculations, I feel that the authors not talking about what the dependent variables were in concrete details disrupted this understanding. [Aditi] Calculated r values - weighted by sample size weighted r values were transformed to Fisher s Z values After aggregation, the averaged Fisher s Z values were transformed back to r values Grand mean and variance of r was calculated first source of variance around the mean r sampling error variance still unexplained variance left moderator variables Assessed the n-r correlation 25

26 4 Results 26

27 Results Overall effect of agency in which avatars were more influential than agents Computed Fisher s Z values from the r values of each DV and submitted all sets of Fisher s Z values to a one-sample t test All DVs 27

28 Results Average effect size per study 28

29 Results Possible factors that influenced the effect sizes Subtracted the sampling error variance from the total variance Resulting variance was greater than zero Likely to be moderator variables to explain part of the variance in the data 29

30 Results Effect of year of publication on the effect of agency Regressed year on the four sets of r values 30

31 Results Effects of Immersion and DV type Submitting the Fisher s Z values of each of the 4 sets to ANOVA Between-DV factors 31

32 Results means and standard errors Pairwise comparisons with Bonferroni corrections 32

33 Results Effect of task type on agency Submitted the Fisher s Z values of all four sets to an ANOVA with task type as a between-dv factor 33

34 Results Pairwise comparisons using Bonferroni corrections r values were higher in both gaming tasks compared to the non-gaming tasks 34

35 Results Actual control made any difference on the effect of the perceived control Fisher s Z values of all four sets to an ANOVA between-dv 35

36 Results Investigated the n-r correlation as a measure of publication bias Significant negative correlations between n and r some studies were not uncovered in the analysis 36

37 5 Implications 37

38 Implications Theoretical HCI Research and Design persuade an audience via a virtual representation to convince them they are interacting with a real person rather than an algorithm Adopt multiple methods of measures 38

39 Implications This might be a good conclusion, might have important implications when designers think about the system. However, the question of how exactly one is supposed to achieve it is as old at the field of computer science itself. Is the goal of the designer here to make sure the software passes the Turing test? Perhaps that was not the idea that the authors were going for, but how else could we put that in the context of avatars vs agents? [Harish] Theoretical HCI Research and Design persuade an audience via a virtual representation to convince them they are interacting with a real person rather than an algorithm Adopt multiple methods of measures 39

40 6 Critique & Discussion 40

41 Critique Strengths agency is an important factor to consider when examining social influence in mediated interactions Multiple Variables Weaknesses Bias of reporting and publishing only significant results Relies on the original researchers execution and reporting did not report system features Few studies - experimental studies - small sample sizes Possible Improvement Role of behavioral realism Investigate how an optimal hybrid can be constructed for different contexts Variable categorizing 41

42 Discussion The paper is easy to read.[nina] I think this is a good example of a meta-analysis. It supports what we learned in class and I had a few of the "aha" moments while reading it.[nina] I liked how the paper cited various forms of virtual representation. The Blascovich study that suggests that user makes a decision without regarding if the avatar is human or computer controlled was an interesting mention. Research questions are well defined based on previous studies.[sourabh] A very easy to understand example for meta-analysis, selection criteria are well defined. [Sourabh] 42

43 Thanks! Any questions? 43