AI, Virtual Worlds, and Massively Multiplayer Online Games Hsinchun CHEN

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AI, Virtual Worlds, and Massively Multiplayer Online Games Hsinchun CHEN View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Institutional Knowledge at Singapore Management University Singapore Management University Institutional Knowledge at Singapore Management University Research Collection School Of Information Systems School of Information Systems 1-2011 Trends and controversies: AI, virtual worlds, and massively multiplayer online games Hsinchun CHEN Yulei ZHANG W. S. Bainbridge Kyong Jin SHIM Singapore Management University, [email protected] N. Pathak See next page for additional authors DOI: https://doi.org/10.1109/MIS.2011.21 Follow this and additional works at: https://ink.library.smu.edu.sg/sis_research Part of the Communication Technology and New Media Commons, and the Graphics and Human Computer Interfaces Commons Citation CHEN, Hsinchun; ZHANG, Yulei; Bainbridge, W. S.; SHIM, Kyong Jin; Pathak, N.; Ahmad, M. A.; DeLong, C.; Borbora, Z.; Mahapatra, A.; and Srivastava, J.. Trends and controversies: AI, virtual worlds, and massively multiplayer online games. (2011). IEEE Intelligent Systems. 26, (1), 80-89. Research Collection School Of Information Systems. Available at: https://ink.library.smu.edu.sg/sis_research/1515 This Journal Article is brought to you for free and open access by the School of Information Systems at Institutional Knowledge at Singapore Management University. It has been accepted for inclusion in Research Collection School Of Information Systems by an authorized administrator of Institutional Knowledge at Singapore Management University. For more information, please email [email protected]. Author Hsinchun CHEN, Yulei ZHANG, W. S. Bainbridge, Kyong Jin SHIM, N. Pathak, M. A. Ahmad, C. DeLong, Z. Borbora, A. Mahapatra, and J. Srivastava This journal article is available at Institutional Knowledge at Singapore Management University: https://ink.library.smu.edu.sg/ sis_research/1515 Published in IEEE Intelligent Systems, 2011 February, Volume 26, Issue 1, Pages 80-89 https://doi.org/10.1109/MIS.2011.21 TRENDS & CONTROVERSIES Editor: Hsinchun Chen, University of Arizona, [email protected] AI, Virtual Worlds, and Massively Multiplayer Online Games Hsinchun Chen, University of Arizona Yulei Zhang, University of Arkansas undreds of thousands of people from dif- of Second Life residents has grown dramatically, ferent physical locations can join virtual with 2.2 million residents in December 2006 and H 8.3 million by August 2007. worlds whenever they want to interact with each Collecting social media data is diffi cult, how- other and create objects in a computer-based ever, because most virtual worlds do not provide simulated environment, typically in an interac- easy data collection functions for regular users. tive 3D format. The rich social media data gener- Most of the data collected by virtual worlds and ated in virtual worlds has important implications MMOGs are proprietary content and are not for business, education, social science, and soci- available for academic research. In an earlier ety at large. Similarly, massively multiplayer on- study, we explored a technical framework to col- line games (MMOGs) have become increasingly lect avatar-related data by using a combination popular and have online communities compris- of bot- and spider-based approaches.4 To demon- ing tens of millions of players. They serve as un- strate our proposed framework, we conducted a precedented tools for theorizing about and empiri- case study on Second Life exploring behavioral cally modeling the social and behavioral dynamics differences between male and female avatars. of individuals, groups, and networks within large Figure 1 shows the proposed framework, where communities.1–3 we use the bot-based approach to collect avatar Some technologists consider virtual worlds and behavioral data and the spider-based approach to MMOGs to be likely candidates to become the collect avatar profi le information. Web 3.0. In such a “brave new world” of diverse The bot-based approach uses LibOpenMetaverse, online virtual civilizations, we believe AI can play a software library for communicating with the a signifi cant role, from multiagent avatar research Second Life server. LibOpenMetaverse lets each and immersive virtual interface design to virtual bot conduct data collection on a much larger scale world and MMOG Web mining and computa- than the basic Linden Script Language (LSL). By tional social science modeling. logging onto the Second Life server using Lib- OpenMetaverse as clients, we used avatars as bots Avatar Data Collection Example to automatically collect other avatars’ behavioral Virtual worlds will become another type of im- data in a given region. We sent a bot to a given portant world in people’s lives in addition to the region where it collected both the behavioral data real world where they physically live. The Gartner and the avatar identifi ers (such as names) at the Group estimated that 80 percent of active Internet same time. The avatar names help the spider-based users will have a “second life” in the virtual world approach collect the avatars’ profi le data. The by the end of 2011 (www.gartner.com/it/page. spider-based approach consists of three compo- jsp?id=503861). Second Life (http://secondlife. nents. Avatar profi le spidering collects the profi le com), developed by Linden Lab and publicly pages of all the avatars whose behavioral informa- launched in 2003, is currently the most popular tion had been gathered using the prior bot-based 3D virtual world. Since its inception, the number approach. Profi le data parsing generates avatar 80 1541-1672/11/$26.00 © 2011 IEEE Ieee InTeLLIGenT SySTeMS Published by the IEEE Computer Society IS-26-01-TandC.indd 80 25/01/11 4:23 PM Improved bot-based approach Avatar data fields including avatar name, behavioral data Avatar behavioral birthday, and picture as well as a data collecting short self-introduction. Lastly, avatar personal data are used to infer ava- Bots Avatar identifiers tars’ other personal characteristics, such as gender and virtual age. Following the proposed integrated Spider-based approach framework, we conducted a case study to examine the differences in Profile data Avatar profile virtual world actions (such as flying, Avatar profile parsing spidering running, and walking) between the two virtual genders—that is, the self- reported gender in virtual worlds. Avatar personal characteristics Avatar personal Avatar names, self-introductions, and extraction/coding characteristics profile pictures were parsed out to three avatar gender coders. Only the avatars whose gender information, either male or female, was able to be Figure 1. Proposed framework for avatar data collection. The bot-based approach collects avatar behavioral data, and the spider-based approach collects avatar clearly decided without any disagree- profile information. ment or confusion among all three coders were kept. Independent group Table 1. Results of the virtual world gender analysis. t-tests were conducted to compare the Male N = 537 Female N = 797 action differences between the two (mean/standard (mean/standard T-test genders as well as two age groups. Avatar action deviation) deviation) (t-stats/p-value) Table 1 shows the analysis results. Flying 0.020 / 0.044 0.015 / 0.037 2.16 / 0.015* For flying (p-value = 0.015), run- Hovering 0.042 / 0.062 0.036 / 0.069 1.51 / 0.065 ning (p-value = 0.023), turning left Running 0.020 / 0.045 0.016 / 0.040 2.00 / 0.023* (p-value = 0.010), turning right (p- value = 0.046), and walking (p-value = Striding 0.018 / 0.028 0.016 / 0.025 1.23 / 0.109 0.005), male avatars were signifi- Turning left 0.099 / 0.071 0.090 / 0.071 2.33 / 0.010** cantly more likely to perform these Turning right 0.095 / 0.071 0.089 / 0.073 1.68 / 0.046* actions than female avatars. Female Walking 0.143 / 0.105 0.129 / 0.099 2.62 / 0.005** avatars were significantly more likely to stand as compared to male ava- Standing 0.775 / 0.161 0.795 / 0.160 −2.26 / 0.012* tars (p-value = 0.012). Male ava- *Significant at 0.05 level. **Significant at 0.01 level. tars seemed more likely to hover and stride, but the results were not statis- patterns. All these data can be read- “Secondary Avatars and Semiautono- tically significant. Overall, male ava- ily obtained (some with further pro- mous Agents,” William S. Bainbridge tars tended to perform more “active” cessing) based on our proposed bot- presents semiautonomous agent as- actions than female avatars. spider framework for virtual world sistants that have been incorporated These findings are consistent with avatar data collection. into recent MMOGs. Although the real people in the physical world, AI behind these agents is basic, their where males are in general more In This Issue behavior in groups and complex sit- physically active than their female This issue includes two articles with uations can provide insights into peers. Our future research will in- additional research examples from how future intelligent systems might volve examining other behavioral distinguished experts in social sci- function in many realms of activity. and avatar characteristics in virtual ence and computer science. Each arti- Bainbridge reports results from ex- worlds, including virtual world ex- cle presents a unique research frame- tensive explorations of two popular perience, age, education level, social work, computational methods, and game worlds, Dungeons and Drag- network formation, and interaction selected results. In the first article, ons Online (DDO) and Star Trek January/february 2011 www.computer.org/intelligent 81 IS-26-01-TandC.indd 81 25/01/11 4:23 PM Second Life,” IEEE Intelligent Systems, vol. 25, no. 4, 2010, pp. 17–23. Hsinchun Chen is the McClelland Profes- sor of Management Information Systems and the director of the Artificial Intelligence Lab at the University of Arizona. Contact him at [email protected].
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