Skip to main content Accessibility help
×
Hostname: page-component-77c89778f8-5wvtr Total loading time: 0 Render date: 2024-07-16T11:30:26.299Z Has data issue: false hasContentIssue false

1 - VERUS: A Multidisciplinary International Behavioral Study of Virtual World Users

from Part I - Individual Behaviors and Dyadic Relationships

Published online by Cambridge University Press:  15 June 2018

Kiran Lakkaraju
Affiliation:
Sandia National Laboratories, New Mexico
Gita Sukthankar
Affiliation:
University of Central Florida
Rolf T. Wigand
Affiliation:
University of Arkansas
Get access

Summary

Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Chapter
Information
Social Interactions in Virtual Worlds
An Interdisciplinary Perspective
, pp. 13 - 42
Publisher: Cambridge University Press
Print publication year: 2018

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abbey, A., Cozzarelli, C., McLaughlin, K., & Harnish, R. J. (1987). The effects of clothing and dyad sex composition on perceptions of sexual intent: Do women and men evaluate these cues differently? Journal of Applied Social Psychology, 17(2), 108126.CrossRefGoogle Scholar
Allen, G. (2000). Men and women, maps and minds: Cognitive bases of sex-related differences in reading and interpreting maps. In Nualláin, S. Ó. (ed.), Spatial cognition: Foundations and applications. Advances in Consciousness Research. Amsterdam: John Benjamins Publishing.Google Scholar
Andreoni, J. (1988). Why free ride? Strategies and learning in public goods experiments. Journal of Public Economics, 37, 291304.Google Scholar
Ardener, S. (1981). Women and space: Ground rules and social maps. London: Croom Helm.Google Scholar
Bergstrom, K., Jenson, J., & de Castell, S. (2012, May). What's ‘choice’ got to do with it? Avatar selection differences between novice and expert players of World of Warcraft and Rift. In Proceedings of the International Conference on the Foundations of Digital Games (pp. 97104). ACM Digital Library.CrossRefGoogle Scholar
Callon, M. (1995). Four models for the dynamics of science. In Jasanoff, S., Markle, G. E., Peterson, J. C., & Pinch, T. J. (eds.), Handbook of science and technology studies (pp. 2963). Cambridge, MA: MIT Press.Google Scholar
Carpenter, J. P., Bowles, S., Gintis, H., & Hwang, S-H. (2009). Strong reciprocity and team production: Theory and evidence. Journal of Economic Behavior and Organization, 71, 221232.Google Scholar
Chee, F., de Castell, S., & Taylor, N. (2011). Public virtual world gaming in Asia: Preparatory fieldwork for site selection, protocol testing and research instrument development. Technical Report 495, Simon Fraser University, BC. Retrieved from: http://summit.sfu.ca/item/495Google Scholar
Chuah, S, Hoffmann, R., & Larner, J. (2013). Elicitation effects in a multi-stage bargaining experiment. Experimental Economics, 17, 335345.CrossRefGoogle Scholar
Chuah, S., Hoffmann, R., & Larner, J. (2016). Perceived intentionality in 2×2 experimental games. Bulletin of Economic Research, in press.Google Scholar
Cover, T., & Thomas, J. (1991). Elements of information theory. New York, NY: John Wiley & Sons.Google Scholar
de Castell, S., Bojin, N., Campbell, S. R., et al. (2010). The eyes have it: Measuring spatial orientation in virtual worlds to explain gender differences in real ones. Technical Report, Simon Fraser University Library, Vancouver, BC.Google Scholar
de Castell, S., Jenson, J., Taylor, N., & Thumlert, K. (2014). Re-thinking foundations: Theoretical and methodological challenges (and opportunities) in virtual worlds research. Journal of Gaming & Virtual Worlds, 6, 1.Google Scholar
de Castell, S., Larios, H., Jenson, J., & Smith, D. H. (2015). The role of video game experience in spatial learning and memory. Journal of Gaming & Virtual Worlds, 7(1), 2140.Google Scholar
Dohmen, T., Falk, A., Huffman, D., Sunde, U., Schupp, J., & Wagner, G. G. (2011). Individual risk attitudes: Measurement, determinants and behavioral consequences. Journal of the European Economic Association, 9(3), 522550.Google Scholar
Dunn, R. A., & Guadagno, R. E. (2012). My avatar and me: Gender and personality predictors of avatar-self discrepancy. Computers in Human Behavior, 28(1), 97106.Google Scholar
Eckel, Catherine C., & Grossman, P. J. (1996). Altruism in anonymous dictator games. Games and Economic Behavior, 16, 181191.Google Scholar
Flach, P., & Lachiche, N. (2001). Confirmation-guided discovery of first-order rules with Tertius. Machine Learning, 42(1/2), 6195.CrossRefGoogle Scholar
Grammer, K., Renninger, L., & Fischer, B. (2004). Disco clothing, female sexual motivation, and relationship status: Is she dressed to impress? Journal of Sex Research, 41(1), 6674.Google Scholar
Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., & Witten, I. H. (2013). Weka 3: Data mining and open source machine learning software in Java.Google Scholar
Hartog, J., Ferrer-i-Carbonell, A., & Jonker, N. (2002). Linking measured risk aversion to individual characteristics. Kyklos, 55(1), 326.Google Scholar
Helbok, C. M., Marinelli, R. P., & Walls, R. T. (2006). National survey of ethical practices across rural and urban communities. Professional Psychology: Research and Practice, 37(1), 3644.CrossRefGoogle Scholar
Hofstede, G. (2001). Culture's consequences: Comparing values, behaviors, institutions, and organizations across nations, 2nd edn. Thousand Oaks, CA: SAGE.Google Scholar
Hussain, Z., & Griffiths, M. D. (2008). Gender swapping and socializing in cyberspace: An exploratory study. CyberPsychology & Behavior, 11(1), 4753.Google Scholar
Inglehart, R. (1997). Modernization and postmodernization: Cultural, economic, and political change in 43 societies. Princeton, NJ: Princeton University Press.Google Scholar
Jenson, J., Bergstrom, K., & de Castell, S. (2013). Playing ‘for Real’: A lab-based study of MMOGs. Selected Papers of Internet Research, 3.Google Scholar
Kennedy, T., Ratan, R. R., Kapoor, K., Pathak, N., Williams, D., & Srivastava, J. (2014). Predicting MMO player gender from in-game attributes using machine learning models. In Predicting real world behaviors from virtual world data (pp. 6984). Cham, Switzerland: Springer International Publishing.Google Scholar
Latour, B. (1992). Where are the missing masses? The sociology of a few mundane artifacts.” In Bilker, W. & Law, J. (eds.), Shaping technology/building society: Studies in sociotechnical change (pp. 225258). Cambridge, MA: MIT Press.Google Scholar
Latour, B. (2005). Reassembling the social: An introduction to actor–network theory. New York, NY: Oxford University Press.CrossRefGoogle Scholar
Lawson, A., Leveque, K., Murray, J., Wang, W., Taylor, N., Jenson, J., & de Castell, S. (2012). Socio-linguistic factors and gender mapping across real and virtual world cultures. Advances in Design for Cross-Cultural Activities, 241.Google Scholar
Lawson, A., & Murray, J. (2014). Identifying user demographic traits through virtual-world language use. In Predicting real world behaviors from virtual world data (pp. 5767). Cham, Switzerland: Springer International Publishing.Google Scholar
Lejuez, C., Read, J., Kahler, C., Richards, J., Ramsey, S., Stuart, G., Strong, D., & Brown, R. (2002). Evaluation of a behavioral measure of risk taking: The balloon analogue risk task (BART), Journal of Experimental Psychology: Applied 8(2), 7584.Google Scholar
Massey, D. (1994). Space, place, and gender. Minneapolis, MN: University of Minnesota Press.Google Scholar
Murray, J., & Arns, D. (2012). Reynard VERUS Research Project – Final Report, US Air Force Research Laboratory, Wright-Patterson AFB OH, RY-WP-TR-2012–0286.Google Scholar
Murray, J, Chow, E., & Connolly, C. (2015). Something in the way we move: Quantifying patterns of exploration in virtual spaces. In Proceedings of Foundation of Digital Games Conference, Pacific Grove, CA.Google Scholar
Prensky, M. (2010). Teaching digital natives: Partnering for real learning. Thousand Oaks, CA: Gorwin.Google Scholar
Rosenfeld, L. B., & Plax, T. G. (1977). Clothing as communication. Journal of Communication 27 (2), 2431.Google Scholar
Symborski, C., Jackson, G. M., Barton, M., Cranmer, G., Raines, B., & Quinn, M. M. (2014). The use of social science methods to predict player characteristics from avatar observations. In Predicting real world behaviors from virtual world data (pp. 1937). Cham, Switzerland: Springer International Publishing.Google Scholar
Tanenbaum, J., Seif El-Nasr, M., & Nixon, M. (2014). Nonverbal communication in virtual worlds: Understanding and designing expressive characters. Pittsburgh, PA: ETC Press.Google Scholar
Taylor, N., de Castell, S., Jenson, J., & Humphrey, M. (2011). Modeling play: Re-casting expertise in MMOGs. In Proceedings of the 2011 ACM SIGGRAPH Symposium on Video Games, August 10, 2011 (pp. 4953). New York, NY: ACM.CrossRefGoogle Scholar
Taylor, N., Jenson, J., de Castell, S., & Dilouya, B. (2014). Public displays of play: Studying online games in physical settings. Journal of Computer-Mediated Communication, 19(4), 763779.Google Scholar
Trepte, S., & Reinecke, L. (2010). Avatar creation and video game enjoyment. Journal of Media Psychology, 22(4), 171184.CrossRefGoogle Scholar
Weka data mining toolset. Machine Learning Group, University of Waikato, NZ. Retrieved from: www.cs.waikato.ac.nz/ml/weka/Google Scholar
Wong, N., Tang, A., Livingston, I., Gutwin, C., & Mandryk, R. (2009). Character sharing in World of Warcraft. In Proceedings of the 11th European Conference on Computer Supported Cooperative Work, September 7–11, 2009, Vienna, Austria.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×