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대규모 다중 사용자 온라인 롤플레잉 게임에서의 
젠더스와핑 현상과 그 영향에 관한 연구 
Gender swapping and its effects in MMORPGs 
박 건 우, 웹사이언스공학전공 석사과정 
지도교수: 차 미 영 
2013. 12. 3. MS thesis defense 1
Background 
• Millions of people have enjoyed MMORPGs 
• MMORPGs provide real-time interactions similar with real-life 
• Research opportunities 
• Human mobility patterns [La and Michiardi, WOSN 2008] 
• Understand the structure [Son et al., PLoS One 2012] 
• Verify social theories [Szell and Thurner, Scientific Report 2013] 
battle conversation trade 
source: http://hohobbang.egloos.com source: garden.egloos.com source: http://www.techspot.com 
2013. 12. 3. MS thesis defense 2
Background 
• Users can freely set their online identities independent of offline identities 
players can set their avatar’s gender 
as opposite to real gender 
2013. 12. 3. MS thesis defense 3
Gender Swapping 
• Users can choose to play with avatars of their opposite gender 
• Notation: Player-Gender.Avatar-Gender 
• 4 possible types: M.M, M.F, F.M, F.F 
• 16 possible types for a give pair 
M.F 
Gender swapper 
F.F 
Straight player 
2013. 12. 3. MS thesis defense 4
Motivation 
• What are the effects of gender swapping on online games? 
• Which gender is more prominent for in-game behaviors? 
• Do players of same gender combination show similar patterns? 
2013. 12. 3. MS thesis defense 5
Previous works 
• Gender swapping is widespread 
• It was firstly observed in text-based MUD (Multi User Dungeon Game) game 
[Bruckeman, 1993] 
• Many gamers have participated in gender swapping 
[Griffith et al. 2004, Hussain and Griffith, 2008] 
• Gender roles in online games 
• Males play for achieving in games, 
while females are motivated to meet new people [Yee, 2006] 
• Males are achievers and females are socializers [Bartle, 1996] 
• Gender differences of in-game behavior and social network 
• Males enjoy longer sessions than females, as same in the Internet [Lo et al. 2005] 
• Male and female manage their networks differently [Szell and Thurner, 2013] 
2013. 12. 3. MS thesis defense 6
Previous works 
• Gender swapping is widespread 
• It was firstly observed in text-based MUD (Multi User Dungeon Game) game 
[Bruckeman, 1993] 
• Many gamers have participated in gender swapping 
[Griffith et al. 2004, Hussain and Griffith, 2008] 
• Gender roles in online games 
Existing researches are conducted by online survey 
• Males play for achieving in games, 
while females are motivated to meet new people [Yee, 2006] 
• Males are achievers and females are socializers [Bartle, 1996] 
Most of them consider only one among two type of gender 
• Gender differences of in-game behavior and social network 
• Males enjoy longer sessions than females, as same in the Internet [Lo et al. 2005] 
• Male and female manage their networks differently [Szell and Thurner, 2013] 
2013. 12. 3. MS thesis defense 7
Research questions 
1. Who participates in gender swapping? 
2. What is the effects of gender swapping on in-game behaviors? 
3. What is the effects of gender swapping on social network structure? 
2013. 12. 3. MS thesis defense 8
Fairyland Online Dataset 
• 17610 avatars owned by 4538 Taiwanese players in 2003 
• Player profiles (offline) – age, gender, zipcode 
• Avatar information (online) – avatar gender, in-game behaviors (level, trade), 
communications 
2013. 12. 3. MS thesis defense 9
Demographic characteristics 
• 1819 (40.3%) players are female 
• quite high fraction than other MMORPGs (16-32%) [Huh and Williams, 2010] 
• Except for 9-13 old, there is no gender difference (p>0.1) 
2013. 12. 3. MS thesis defense 10
Who participates in gender swapping? 
2013. 12. 3. MS thesis defense 11
Who participates in gender swapping? 
Correlation with gender 
• Is there differences of gender swapping ratio across gender? 
Gender 
Experienced 
gender swapping 
gender swapper 
Male 957 37.0% 
Female 791 45.3% 
Total 1748 40.3% 
• Method: Chi-square test 
• Females are more likely to swap genders (p<0.001) 
Fraction of 
2013. 12. 3. MS thesis defense 12
Who participates in gender swapping? 
Correlation of player maturity in game and real world 
• Basis 
• Age 
• Number of avatars a player owned 
• Method 
• See fraction of gender-swapped 
avatar among all avatars a player has 
• Older players are more likely to 
swap genders than younger players 
• Players with many avatars are 
likelier to swap genders 
2013. 12. 3. MS thesis defense 13
Who participates in gender swapping? 
• Gender swapping is widespread 
• Females participate in gender swapping more than males 
• Older players and experienced players are more likely to swap gender 
2013. 12. 3. MS thesis defense 14
What are the effects of gender swapping 
on in-game behaviors? 
source: http://garden.egloos.com source: http://www.techspot.com 
2013. 12. 3. MS thesis defense 15
Effects of gender swapping on in-game behaviors 
Level-up: achievements in game 
Q. Who do achieve levels faster than others? 
• Method 
• Using session time (online active time) 
• Kolmogorov-Smirnov test (K-S test) 
• Male players level up more quickly than female players (D=0.0611 and p<0.01) 
• Female players with male avatars show the fastest level-up (D=0.1824 and p<0.001) 
2013. 12. 3. MS thesis defense 16
Effects of gender swapping on in-game behaviors 
Level-up: achievements in game 
Q. Who do achieve levels faster than others? 
source: http://garden.egloos.com 
• Method 
• Using session time (online active time) 
• Kolmogorov-Smirnov test (K-S test) 
Level-up follows gender role in both world 
• Male players level up more quickly than female players (D=0.0611 and p<0.01) 
• Female players with male avatars show the fastest level-up (D=0.1824 and p<0.001) 
2013. 12. 3. MS thesis defense 17
Effects of gender swapping on in-game behaviors 
Trade: economic gains 
Q. Who does get a better deal? 
• Market price of the five most traded items and their expected gains 
• Female avatars tend to profit more in trades 
2013. 12. 3. MS thesis defense 18
Effects of gender swapping on in-game behaviors 
Trade: economic gains 
Q. Who does get a better deal? 
source: http://www.techspot.com 
• Market price of the five most traded items and their expected gains 
• Female avatars tend to profit more in trades 
Trade follows gender role in the online world 
2013. 12. 3. MS thesis defense 19
What are the effects of gender swapping on 
in-game behaviors? 
• Players swap avatar’s genders to get benefits of opposite gender 
[Bartle. 1996, Bruckman. 1993, Wang and Wang. 2008, Zaheer and Grifffiths. 2008] 
• Female: to achieve 
• Male: to get advantages of trade 
• Both real and virtual gender affect in-game behaviors 
2013. 12. 3. MS thesis defense 20
What are the effects of gender swapping 
on social network structure? 
2013. 12. 3. MS thesis defense 21
Effects of gender swapping on social network structure 
Dyadic relationship 
 Whisper: one-to-one private communication 
M.F 
• Method: the odd ratio against random expectations on whisper communication 
• Players are more likely to send messages to opposite-gender avatars 
2013. 12. 3. MS thesis defense 22
Effects of gender swapping on social network structure 
Dyadic relationship 
 Chat length against gender combination 
• Female players chat longer than male players 
• Chats are longer between opposite-gender avatars 
2013. 12. 3. MS thesis defense 23
Effects of gender swapping on social network structure 
Dyadic relationship 
 Friendship: sustained relationship 
M.F 
• Method: the odd ratio against random expectations on friendship 
• Players whose gender are same with each other tend to become friends 
• Controlling for player genders, the players were slightly likelier to form a friendship tie 
when their avatars had opposite genders. 
• For friendship formation, offline genders have more significant effects than online 
2013. 12. 3. MS thesis defense 24
Effects of gender swapping on social network structure 
Triangular relationship 
 Fully connected triangular relationship against gender combinations 
• Method 
• Construction of network using friendship having at least one whisper communication 
• Calculate the odd ratio against random expectation 
• Heterogeneity of avatar gender is more preferred (p<0.01, for top users, p<0.001) 
• Triangles consisting of two male and one female avatars are more easily formed than triangle of 
one-male and two female avatars 
• similar trends are observed in two social networking services (Facebook and Weibo) [in Appendix] 
2013. 12. 3. MS thesis defense 25
What are the effects of gender swapping 
on network structure? 
• Both in-game gender and real gender have an impact on dyadic relationship 
• For triadic relationship, gender role of avatar is more followed 
2013. 12. 3. MS thesis defense 26
Conclusion 
2013. 12. 3. MS thesis defense 27
Implication 
• Gender swapping provides another point to view online games 
• It gives clues to understand various behaviors and network patterns 
• The result shows similar trend with real world’s pattern 
• It supports that MMORPG is a good platform to conduct user behavior research 
as well as social network analysis 
• Potential application 
• Bot detection: use gender-related features to boost accuracy 
• Online identity fraud detection: find sexual deviants or predators 
2013. 12. 3. MS thesis defense 28
Limitation 
• Limited to analysis on an instance of MMORPG 
• Hard to generalize 
• Sample bias: Taiwanese users 
• Can expand to studies on culture differences in future works 
2013. 12. 3. MS thesis defense 29
Future works 
• Similar analysis on other MMORPGs 
• Understanding differences of language usages across gender combination 
• Investigating identity differences between real world and web services 
2013. 12. 3. MS thesis defense 30
Publications 
• Researches on Gender Swapping 
• J-K. Lou, K. Park, M. Cha, J. Park, C-L. Lei, K-T. Chen. 
Gender Swapping and User Behaviors in Online Social Games. 
In proc. of the 22th International Conference on World Wide Web (WWW),2013. 
• J-K. Lou, K. Park, K-T. Chen, J. Park, M. Cha. 
Social Networks and Hidden Node Information: Gender Swapping. 
In proc. of Workshop on Information in Network (WIN), 2013. 
• Other studies 
• K. Park, S. Lee, E. Kim, M. Park, J. Park, M. Cha. 
Mood and Weather: Feeling the Heat? 
In proc. of the 7th International AAAI Conference on Weblogs and Social Media 
(ICWSM), 2013 (poster). 
• K. Park, J. Park, S. Park, J. Kim, S. Kwon, J. Kwak, M. Cha. 
Voice of the Employees Resonated in Online Bamboo Forests. 
In 7th International AAAI Conference on Weblogs and Social Media (ICWSM) 
Workshop on Social Computing for Workforce 2.0, 2013. 
2013. 12. 3. MS thesis defense 31
감사합니다. 
2013. 12. 3. MS thesis defense 32
Appendix 
2013. 12. 3. MS thesis defense 33
MMORPG player statistics 
source: http://MMOdata.net 
2013. 12. 3. MS thesis defense 34
Demographic characteristics 
• A quite large fraction of players 
live in rural areas (31.25%) 
• Gender ratios are nearly 
consistent across regions 
(p>0.01) 
2013. 12. 3. MS thesis defense 35
Who participate in gender swapping? 
Correlation with geography 
• Are people who live in urban more likely to swap genders? 
Region 
Experienced 
gender swapping 
Fraction of 
gender swapper 
Urban 1212 40.7% 
Rural 536 35.6% 
Total 1748 40.3% 
• Gender swapping ratio was nearly consistent in rural and urban areas (p=0.5697) 
2013. 12. 3. MS thesis defense 36
Triangular analysis on Weibo 
• User: 2286 – 1302 males (56.96%), 984 females (43.04%) 
• Link: 3265 
2013. 12. 3. MS thesis defense 37
Triangular analysis on Facebook 
• User: 50016 - 23137 males (46.26%), 26879 females (53.74%) 
• Link: 154568 
2013. 12. 3. MS thesis defense 38

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MS thesis defense - Gender swapping and its effects in MMORPGs

  • 1. 대규모 다중 사용자 온라인 롤플레잉 게임에서의 젠더스와핑 현상과 그 영향에 관한 연구 Gender swapping and its effects in MMORPGs 박 건 우, 웹사이언스공학전공 석사과정 지도교수: 차 미 영 2013. 12. 3. MS thesis defense 1
  • 2. Background • Millions of people have enjoyed MMORPGs • MMORPGs provide real-time interactions similar with real-life • Research opportunities • Human mobility patterns [La and Michiardi, WOSN 2008] • Understand the structure [Son et al., PLoS One 2012] • Verify social theories [Szell and Thurner, Scientific Report 2013] battle conversation trade source: http://hohobbang.egloos.com source: garden.egloos.com source: http://www.techspot.com 2013. 12. 3. MS thesis defense 2
  • 3. Background • Users can freely set their online identities independent of offline identities players can set their avatar’s gender as opposite to real gender 2013. 12. 3. MS thesis defense 3
  • 4. Gender Swapping • Users can choose to play with avatars of their opposite gender • Notation: Player-Gender.Avatar-Gender • 4 possible types: M.M, M.F, F.M, F.F • 16 possible types for a give pair M.F Gender swapper F.F Straight player 2013. 12. 3. MS thesis defense 4
  • 5. Motivation • What are the effects of gender swapping on online games? • Which gender is more prominent for in-game behaviors? • Do players of same gender combination show similar patterns? 2013. 12. 3. MS thesis defense 5
  • 6. Previous works • Gender swapping is widespread • It was firstly observed in text-based MUD (Multi User Dungeon Game) game [Bruckeman, 1993] • Many gamers have participated in gender swapping [Griffith et al. 2004, Hussain and Griffith, 2008] • Gender roles in online games • Males play for achieving in games, while females are motivated to meet new people [Yee, 2006] • Males are achievers and females are socializers [Bartle, 1996] • Gender differences of in-game behavior and social network • Males enjoy longer sessions than females, as same in the Internet [Lo et al. 2005] • Male and female manage their networks differently [Szell and Thurner, 2013] 2013. 12. 3. MS thesis defense 6
  • 7. Previous works • Gender swapping is widespread • It was firstly observed in text-based MUD (Multi User Dungeon Game) game [Bruckeman, 1993] • Many gamers have participated in gender swapping [Griffith et al. 2004, Hussain and Griffith, 2008] • Gender roles in online games Existing researches are conducted by online survey • Males play for achieving in games, while females are motivated to meet new people [Yee, 2006] • Males are achievers and females are socializers [Bartle, 1996] Most of them consider only one among two type of gender • Gender differences of in-game behavior and social network • Males enjoy longer sessions than females, as same in the Internet [Lo et al. 2005] • Male and female manage their networks differently [Szell and Thurner, 2013] 2013. 12. 3. MS thesis defense 7
  • 8. Research questions 1. Who participates in gender swapping? 2. What is the effects of gender swapping on in-game behaviors? 3. What is the effects of gender swapping on social network structure? 2013. 12. 3. MS thesis defense 8
  • 9. Fairyland Online Dataset • 17610 avatars owned by 4538 Taiwanese players in 2003 • Player profiles (offline) – age, gender, zipcode • Avatar information (online) – avatar gender, in-game behaviors (level, trade), communications 2013. 12. 3. MS thesis defense 9
  • 10. Demographic characteristics • 1819 (40.3%) players are female • quite high fraction than other MMORPGs (16-32%) [Huh and Williams, 2010] • Except for 9-13 old, there is no gender difference (p>0.1) 2013. 12. 3. MS thesis defense 10
  • 11. Who participates in gender swapping? 2013. 12. 3. MS thesis defense 11
  • 12. Who participates in gender swapping? Correlation with gender • Is there differences of gender swapping ratio across gender? Gender Experienced gender swapping gender swapper Male 957 37.0% Female 791 45.3% Total 1748 40.3% • Method: Chi-square test • Females are more likely to swap genders (p<0.001) Fraction of 2013. 12. 3. MS thesis defense 12
  • 13. Who participates in gender swapping? Correlation of player maturity in game and real world • Basis • Age • Number of avatars a player owned • Method • See fraction of gender-swapped avatar among all avatars a player has • Older players are more likely to swap genders than younger players • Players with many avatars are likelier to swap genders 2013. 12. 3. MS thesis defense 13
  • 14. Who participates in gender swapping? • Gender swapping is widespread • Females participate in gender swapping more than males • Older players and experienced players are more likely to swap gender 2013. 12. 3. MS thesis defense 14
  • 15. What are the effects of gender swapping on in-game behaviors? source: http://garden.egloos.com source: http://www.techspot.com 2013. 12. 3. MS thesis defense 15
  • 16. Effects of gender swapping on in-game behaviors Level-up: achievements in game Q. Who do achieve levels faster than others? • Method • Using session time (online active time) • Kolmogorov-Smirnov test (K-S test) • Male players level up more quickly than female players (D=0.0611 and p<0.01) • Female players with male avatars show the fastest level-up (D=0.1824 and p<0.001) 2013. 12. 3. MS thesis defense 16
  • 17. Effects of gender swapping on in-game behaviors Level-up: achievements in game Q. Who do achieve levels faster than others? source: http://garden.egloos.com • Method • Using session time (online active time) • Kolmogorov-Smirnov test (K-S test) Level-up follows gender role in both world • Male players level up more quickly than female players (D=0.0611 and p<0.01) • Female players with male avatars show the fastest level-up (D=0.1824 and p<0.001) 2013. 12. 3. MS thesis defense 17
  • 18. Effects of gender swapping on in-game behaviors Trade: economic gains Q. Who does get a better deal? • Market price of the five most traded items and their expected gains • Female avatars tend to profit more in trades 2013. 12. 3. MS thesis defense 18
  • 19. Effects of gender swapping on in-game behaviors Trade: economic gains Q. Who does get a better deal? source: http://www.techspot.com • Market price of the five most traded items and their expected gains • Female avatars tend to profit more in trades Trade follows gender role in the online world 2013. 12. 3. MS thesis defense 19
  • 20. What are the effects of gender swapping on in-game behaviors? • Players swap avatar’s genders to get benefits of opposite gender [Bartle. 1996, Bruckman. 1993, Wang and Wang. 2008, Zaheer and Grifffiths. 2008] • Female: to achieve • Male: to get advantages of trade • Both real and virtual gender affect in-game behaviors 2013. 12. 3. MS thesis defense 20
  • 21. What are the effects of gender swapping on social network structure? 2013. 12. 3. MS thesis defense 21
  • 22. Effects of gender swapping on social network structure Dyadic relationship  Whisper: one-to-one private communication M.F • Method: the odd ratio against random expectations on whisper communication • Players are more likely to send messages to opposite-gender avatars 2013. 12. 3. MS thesis defense 22
  • 23. Effects of gender swapping on social network structure Dyadic relationship  Chat length against gender combination • Female players chat longer than male players • Chats are longer between opposite-gender avatars 2013. 12. 3. MS thesis defense 23
  • 24. Effects of gender swapping on social network structure Dyadic relationship  Friendship: sustained relationship M.F • Method: the odd ratio against random expectations on friendship • Players whose gender are same with each other tend to become friends • Controlling for player genders, the players were slightly likelier to form a friendship tie when their avatars had opposite genders. • For friendship formation, offline genders have more significant effects than online 2013. 12. 3. MS thesis defense 24
  • 25. Effects of gender swapping on social network structure Triangular relationship  Fully connected triangular relationship against gender combinations • Method • Construction of network using friendship having at least one whisper communication • Calculate the odd ratio against random expectation • Heterogeneity of avatar gender is more preferred (p<0.01, for top users, p<0.001) • Triangles consisting of two male and one female avatars are more easily formed than triangle of one-male and two female avatars • similar trends are observed in two social networking services (Facebook and Weibo) [in Appendix] 2013. 12. 3. MS thesis defense 25
  • 26. What are the effects of gender swapping on network structure? • Both in-game gender and real gender have an impact on dyadic relationship • For triadic relationship, gender role of avatar is more followed 2013. 12. 3. MS thesis defense 26
  • 27. Conclusion 2013. 12. 3. MS thesis defense 27
  • 28. Implication • Gender swapping provides another point to view online games • It gives clues to understand various behaviors and network patterns • The result shows similar trend with real world’s pattern • It supports that MMORPG is a good platform to conduct user behavior research as well as social network analysis • Potential application • Bot detection: use gender-related features to boost accuracy • Online identity fraud detection: find sexual deviants or predators 2013. 12. 3. MS thesis defense 28
  • 29. Limitation • Limited to analysis on an instance of MMORPG • Hard to generalize • Sample bias: Taiwanese users • Can expand to studies on culture differences in future works 2013. 12. 3. MS thesis defense 29
  • 30. Future works • Similar analysis on other MMORPGs • Understanding differences of language usages across gender combination • Investigating identity differences between real world and web services 2013. 12. 3. MS thesis defense 30
  • 31. Publications • Researches on Gender Swapping • J-K. Lou, K. Park, M. Cha, J. Park, C-L. Lei, K-T. Chen. Gender Swapping and User Behaviors in Online Social Games. In proc. of the 22th International Conference on World Wide Web (WWW),2013. • J-K. Lou, K. Park, K-T. Chen, J. Park, M. Cha. Social Networks and Hidden Node Information: Gender Swapping. In proc. of Workshop on Information in Network (WIN), 2013. • Other studies • K. Park, S. Lee, E. Kim, M. Park, J. Park, M. Cha. Mood and Weather: Feeling the Heat? In proc. of the 7th International AAAI Conference on Weblogs and Social Media (ICWSM), 2013 (poster). • K. Park, J. Park, S. Park, J. Kim, S. Kwon, J. Kwak, M. Cha. Voice of the Employees Resonated in Online Bamboo Forests. In 7th International AAAI Conference on Weblogs and Social Media (ICWSM) Workshop on Social Computing for Workforce 2.0, 2013. 2013. 12. 3. MS thesis defense 31
  • 32. 감사합니다. 2013. 12. 3. MS thesis defense 32
  • 33. Appendix 2013. 12. 3. MS thesis defense 33
  • 34. MMORPG player statistics source: http://MMOdata.net 2013. 12. 3. MS thesis defense 34
  • 35. Demographic characteristics • A quite large fraction of players live in rural areas (31.25%) • Gender ratios are nearly consistent across regions (p>0.01) 2013. 12. 3. MS thesis defense 35
  • 36. Who participate in gender swapping? Correlation with geography • Are people who live in urban more likely to swap genders? Region Experienced gender swapping Fraction of gender swapper Urban 1212 40.7% Rural 536 35.6% Total 1748 40.3% • Gender swapping ratio was nearly consistent in rural and urban areas (p=0.5697) 2013. 12. 3. MS thesis defense 36
  • 37. Triangular analysis on Weibo • User: 2286 – 1302 males (56.96%), 984 females (43.04%) • Link: 3265 2013. 12. 3. MS thesis defense 37
  • 38. Triangular analysis on Facebook • User: 50016 - 23137 males (46.26%), 26879 females (53.74%) • Link: 154568 2013. 12. 3. MS thesis defense 38

Editor's Notes

  1. 안녕하세요. 웹사이언스공학전공 석사과정 박건우입니다. 저는 ‘대규모 다중 사용자 온라인 롤플레잉 게임에서의 젠더스와핑 현상과 그 영향에 관한 연구’라는 주제로 석사 연구를 진행하였습니다. 저는 차미영 교수님의 지도를 받고 있으며 박주용 교수님께서도 많은 연구 지도를 해주셨습니다. 그럼, 지금부터 석사논문 디펜스를 진행하겠습니다.
  2. 웹과 인터넷의 급속한 발전에 힘입어, MMORPG, 즉 대규모 다중 사용자 온라인 롤플레잉 게임은 수백만의 사용자가 플레이하게 되었습니다. 이런 MMORPG환경은 실제 삶과 유사한 환경을 제공하게 되고, 이런 가상의 세상속에서 사람들은 서로서로 대화하고, 거래하고, 그리고 공동의 몬스터를 물리치기 위해 협동하며 싸우기도 합니다. 이런 삶과 유사한 환경에서 일어나는 가상적인 세상이 행동학적 연구, 네트워크 분석 연구 등 데이터를 이용한 연구의 가능성을 제공합니다. 최근에는 대표적으로 게임을 통해 사람의 이동 패턴을 이해하고 네트워크 구조를 이해하고 다양한 이론들을 검증하고자 하는 연구들이 이루어졌습니다. MMORPG에 관련된 연구를 분류해 보면 크게 소셜 사이언스에서의 연구 그리고 컴퓨터 사이언스에서의 연구를 들수 있습니다. 컴퓨터 사이언스에서는 네트워크 트래픽 분석, 봇 디텍션 등 게임 시스템 자체에 관한 연구들이 많이 수행되었습니다. 소셜 사이언스에서의 연구는 가상적 세상을 통해 실 세상의 사용자의 행동을 이해하고, 네트워크를 이해하고자 하는 연구들이 주로 이루어졌으며 이들 대부분은 소규모의 온라인 서베이를 기반으로 연구가 이루어졌으나 최근 데이터를 이용한 연구들이 많이 이루어지고 있습니다.
  3. 이런 가상의 온라인 게임 세상에서, 사용자들은 자신들의 아바타를 통해 행동하게 됩니다. 이러한 아바타들은 사용자가 원하는대로, 즉 온라인 아이덴티티를 오프라인과 독립적으로 설정할 수 있는 특징을 가지고 있습니다. 이 예는 실제 온라인 게임에서 캐릭터를 생성하기 위한 화면인데요. 직업, 종족을 자유롭게 선택할 수 있으며, 아바타의 외관또한 자유롭게 설정할 수 있습니다. 그리고 심지어는 게임 내 캐릭터의 성별 또한 자유롭게 선택할 수 있어 실제 성별과 반대로 설정 또한 가능합니다. 예를 들어 저는 남자이지만 게임 내에서는 여성 캐릭터를 이용해 플레이할 수도 있는 것입니다.
  4. 이 현상을 젠더스와핑 현상이라고 하며, 이것은 반대 성별의 아바타를 이용해 플레이하는 현상을 의미합니다. 즉, 이런 재미있는 상황을 생각해 볼 수 있습니다. 온라인 게임 내에서 두명의 여성 아바타가 대화를 하고 있습니다. 서로 여성 플레이어라고 생각하고 대화를 하였으나 실제로는 한 아바타는 여성 플레이어에 의해, 다른 아바타는 남성 아바타에 의해 조종되고 있었습니다. 즉 이 플레이어는 straight player, 이 플레이어는 gender swapper인 것입니다. 이후에도 편의를 위해 이 표기법을 사용하도록 하겠습니다. 처음이 플레이어 성별.두번째가 아바타 성별입니다.
  5. 그럼 이런 젠더 스와핑으로 인해 나타나는 다양한 성별의 조합이 게임내 어떤 영향을 미칠까요? 어떤 성별이, 게임 내 행동을 통해 더 잘 드러나게 되는 것일까요?
  6. 기존에 젠더 스와핑 현상은 텍스트 기반의 MUD게임에서 처음 발견되었습니다. 그 이후 많은 사람들이 젠더 스와핑에 참여하고 있다는 연구들이 발표되었습니다. 한편 온라인 게임에서의 성 역할과 성별의 차이에 관한 연구들도 기존에 많이 이루어져 왔는데요. 남자들은 주로 성취를 위해 온라인 게임을 플레이하고, 여자들은 새로운 사람들을 만나기 위해 게임을 플레이한다는 연구들이 있었습니다. 즉 1996년에 바틀이 발표한 연구에 따르면 남성 사용자는 achiever, 여성 사용자는 socializer로 분류가 될 수 있는 것입니다. 이런 성별의 차이는 게임내 행동과 소셜 네트워크를 통해서도 다양하게 드러나왔습니다.
  7. 이렇듯 다양하게 성별 차이와, 젠더 스와핑에 대한 연구가 이루어져 왔으나 기존의 연구들은 소규모 그룹을 대상으로한 온라인 서베이 혹은 인터뷰로 이루어져 와 self-selection bias, self-reporting bias등의 위험이 있습니다. 또한 성별차이에 관한 대부분의 연구들이 온라인, 오프라인 성별을 동시에 고려하지 않았다는 한계점들이 존재합니다.
  8. 이 연구에서 풀고자 하는 문제들은 다음과 같습니다. 첫째. 젠더 스와핑에 누가 주로 참여하는가. 둘째. 게임내 행동에 있어서 젠더스와핑이 주는 영향이 무엇이며 어떻게 패턴이 드러나는가. 그리고 마지막으로 소셜 네트워크 패턴에 있어서 젠더스와핑의 영향이 무엇이고 그것에 의해 드러나는 패턴을 보이고자 하였습니다.
  9. 이 연구를 위해 Fairyland Online이라는 온라인 게임 데이터를 이용하였습니다. 4538명의 대만 사용자들이 17610개의 아바타를 통해 플레이한 전체 데이터를 이용하였습니다. 해당 데이터셋은 실제 게임을 플레이한 사용자들의 나이, 성별, 사는 위치 등의 정보와 게임 내에서 사용한 아바타의 성별, 게임 내 행동들 그리고 커뮤니케이션 등의 데이터로 구성됩니다.
  10. 게임을 플레이한 사용자들의 인구통계학적 특성은 다음과 같습니다. 다른 온라인 게임들과는 다르게 여성 사용자들의 비율이 상당히 높았습니다. 약 40% 정도의 사용자가 여성 사용자였습니다. 초등학생 정도의 나이인 9~13세를 제외하고는 남녀 성비에 큰 차이가 없습니다. 성비가 골고루 분포되어있다는 점에서 이는 젠더스와핑을 보기에 적절한 데이터 셋이라 할 수 있습니다.
  11. 그렇다면, 누가 젠더 스와핑에 참여한 것일까요? (3초 pause)
  12. 이를 위해 플레이어의 오프라인 정보와 젠더 스와핑의 비율을 살펴 보았습니다. 첫째로 성별을 보았는데요. 과연, 남자가 젠더스와핑에 많이 참여할까요, 혹은 여성이 더 많이 참여할까요? 이 분석을 위해 chi square-test를 이용해 통계적 차이를 살펴보았습니다. 결과는 여성이 더 아바타의 성별을 바꿔 플레이하는 것으로 나왔습니다. 이는 기존의 연구에서 밝혀졌던 것과 일치하는 결과를 보여주고 이습니다. ----- Meeting Notes (2013. 12. 1. 00:10) ----- 관련연구 추가 (여성이 많다)
  13. 이어 플레이어의 나이와, 게임 내 아바타 수에 따른 젠더 스와핑의 비율을 살펴보았습니다. 첫째로 나이와 젠더 스와핑의 관계를 보았습니다. 나이와 이 관계는 어떻게 될까요? 나이가 많을 수록 젠더 스와핑에 더 참여하는 경향성을 보였습니다. 이 그래프의 각 색은 젠더 스와핑을 한 아바타의 비율을 나타냅니다. 즉 빨간색은 한 플레이어가 5개의 아바타를 통해 플레이를 하였을 때, 5개 모두 젠더 스왑된 아바타임을 의미합니다. 이 그래프의 위쪽을 보시면 나이에 따라 더 많이 젠더 스와핑을 하고 있음을 관찰할 수 있습니다. 이어서 보유한 아바타 수에 따른 젠더 스와핑의 경향성을 보았습니다. 한 플레이어는 여러 개의 아바타를 가질 수 있고, 보유한 아바타의 수가 많을 수록 게임을 더 많이 경험하였다고 생각할 수 있을 것입니다. 결과는 많은 아바타로 플레이한 사람일 수록 젠더 스와핑에 더 많이 참여하는 것으로 나타났습니다. 즉 게임을 많이 플레이한 사람들이 젠더 스와핑에 적극적으로 참여하고 있고, 이는 젠더 스와핑이 단순히 한번 해보는 행동이 아님을 보여주고 있습니다.
  14. 많은 사람들이 젠더 스와핑이라는 흥미로운 현상에 참여하고 있으며, 특히 여성 사용자들이 남성보다 많이 참여하였습니다. 그리고 나이가 많을 수록, 그리고 게임 내 경험이 많을수록 젠더를 스왑하는 경향성을 보였는데 이는 그들이 젠더 스와핑의 게임내 베네핏을 알지도 모른다는 것을 암시하고 있습니다.
  15. 그럼, 젠더 스와핑은 게임내 행동들에 어떤 영향을 미치고 있을까요? (pause 3초) 이를 보기 위해 크게 두 가지의 게임 내 행동들을 분석하였습니다.
  16. 첫째는 레벨 업 입니다. 레벨 업은 게임 내에서의 성취로써 게임을 플레이하는 주 목적으로 많이 여겨지게 됩니다. 게임의 일반적인 목표는 몬스터들을 물리치며 레벨 업을 하고, 더 강한 몬스터를 물리치는 것입니다. 즉 레벨업은 게임내 성취를 나타내는 것으로 볼수 있습니다. 그렇다면 어떤 성별의 사용자가 레벨업을 빠르게 할까요? 이 그래프는 각 레벨에 이르기 까지 걸린 시간들의 통계값을 보여주고 있습니다. 이 그래프에서의 노란 바는 여성 아바타로 플레이한 여성 플레이어, 그리고 각각의 색은 실제 성별과 아바타 성별의 조합을 나타냅니다. 각 레벨에 이르기까지 걸린시간을 측정하기 위해 session time, 즉 online active time을 이용하였습니다. 그리고 각 성별 조합에 따른 레벨 속도를 비교하기 위해 K-S test를 이용하였습니다. 우리가 일반적으로 생각하고, 기존 연구에서도 드러낫듯이, 남성 플레이어의 경우 여성 플레이어들보다 빠른 레벨업 속도를 보입니다. 이는 Bartle에 의해 분류된 남성 플레이어의 타입이 achiever인 것과도 일치하는 결과입니다. 그 경향성은 아바타를 통해서도 드러납니다. 플레이어의 성별에 관계없이 남성 아바타가 여성 아바타보다 빠른 레벨업 속도를 보였습니다. 여성 플레이어가 남성 아바타로 플레이하였을때 가장 빠른 속도를 보였습니다. 이는 기존에 젠더스와핑의 모티베이션에 관한 연구에서 스와퍼들은 상대 성별의 이득을 누리기 위해 젠더 스와핑을 한다고 대답했던 것과 일치하는 결과입니다. 즉, 여성 플레이어들이 여성 아바타로 플레이하였을 때는 다른 사용자들이 많이 말을 거는 등, 레벨업 속도가 늦어지게 되는데 이런 여성 유저들의 특성 상, 레벨업을 빨리하고 싶을 때 남성 아바타로 플레이할 수 있는 것이죠.
  17. 이어서 트레이드에서 나타나는 성별의 차이를 보았습니다. 트레이드는 게임 내에서 사용자들 간에 일어나는 거래를 의미합니다. 각 거래에서 사용자들은 실 세상처럼 필요한 아이템을 돈을 주고 사고 팔게 됩니다. 그럼 이런 거래에서 이득을 보는 아바타의 성별, 혹은 플레이어의 성별이 있을까요? 이 테이블은 가장 많이 트레이드된 5개의 아이템의 시장 가격과 성별에 따른 이득의 기대값을 보여줍니다. 뚜렷한 경향성을 보여주고 있지는 않지만, 플레이어 성별을 통제하였을 때, 여성아바타로 플레이하였을때 더 이득을 보는 경향성을 보여줍니다.
  18. 즉 거래에 있어서는 아바타의 성 역할을 따라가고 있는 것입니다.
  19. 즉, 게임을 플레이하는 사람들은 상대 성별의 이득을 얻기위해 반대 성별의 아바타로 플레이하는 경향을 보여줍니다. 여성은 더 빠른 성취를 위해, 남성은 거래의 이득을 취하기 위해 성별을 바꿔 플레이하게 되는 것이죠. 이는 기존의 서베이, 인터뷰 기반의 연구들과 일치하는 결과입니다. 다시 말해 실제 성별과 아바타의 성별 모두 게임내 행동의 패턴에 있어 뚜렷한 차이를 보여주고 있습니다.
  20. 온라인 게임은 사람들이 많이 모여있는 또 하나의 세계이며, 이 세상 속에서 사람들은 대화하고, 협동하며 플레이하게 됩니다. 즉 소셜 네트워크를 이루게 됩니다. 그렇다면 젠더 스와핑은 이런 소셜 네트워크의 구조적 패턴에 어떤 영향을 미치고 있을까요? (pause 3초)
  21. 첫째로 dyad, 즉 한 쌍의 관계에서 나타나는 경향성을 살펴보았습니다. 게임 내에서 사용자들은 귓속말이라고 하는, 남에게 보이지 않는 1대1 메시지를 보낼 수 있는데요, 어떤 성별에서 어떤 성별으로 많이 보내게 될까요? 이를 위해 랜덤 값에 비해서 얼마나 더 많은 메시지가 보내졌는지, 즉 odd ratio를 이용하였습니다. 이런 메시지를 보내는 관계에서 성별에 따른 뚜렷한 경향성이 나타났습니다. 실제 어떤 성별의 아바타로 플레이하든 관계없이 자신과 다른 성별의 아바타에게 메시지를 많이 보냈습니다. 즉, 저는 게임 내에서 어떤 성별의 아바타로 플레이하든 관계없이 여성 아바타에게 메시지를 더 많이 보내게 되는 것입니다. 이는 메시지를 전송한 사람이 여성인 경우에도 똑같이 나타났습니다.
  22. 메시지의 전송이 뚜렷한 패턴을 보여주고 있지만, 단순한 메시지의 전송은 무작위로 알지도 못하는 사람들에게 보낼수 잇는 것이기 때문에 어떠한 귓속말들은 한번 보내고 대화가 이루어지지 않을 수 있습니다. 따라서 대화가 이루어진 페어들을 대상으로 대화의 길이를 분석해 보았습니다. 결과는 여성 사용자들간의 대화가 남성 사용자간의 대화, 그리고 남여간의 대화 보다 더 길게 나타났습니다. 여성의 경우 더 소셜하다는 것을 보여주고 있습니다. 하지만 아바타의 성별은 이러한 경향 중에서도 영향을 미쳤습니다. 다른 성별을 가진 아바타간의 대화가 실제 성별을 통제하였을 때 더 긴 대화 길이를 보였습니다. 이는 대화와 같은 소셜 스킬이 필요한 것에서는 실제 성별이 주로 영향을 미치지만, 온라인 세상에서의 가상적인 성별 또한 소셜 네트워크 패턴에 영향을 미치고 있음을 보여주는 결과입니다.
  23. 이러한 경향성은 친구 관계를 맺는 것에서는 어떻게 드러날까요. 일방적으로 보낼수 있는 귓속말 메시지와는 다르게, 친구 관계는 상호 동의에 의해 이루어지며 명시적으로 관리되는 관계입니다. 이 분석을 위해 귓속말 분석을 하였을 때와 동일한 방법으로 random expectatio과 비교하여 odd ratio를 분석하였습니다. 귓속말 메시지를 보낼때에는 상대 성별의 아바타들에게 많이 보냈던 반면에, 실제 같은 성별간의 쌍일 경우에 친구 관계가 맺어졌습니다. 또한 아바타 성별의 영향도 조금은 있었습니다. 플레이어 성별을 통제하였을 때, 상대 성별을 가진 아바타와 약간 더 많이 친구관계가 맺어지는 경향을 보였습니다. 정리하자면 친구관계에 있어서는 오프라인 성별이 온라인 성별보다는 더 강한 영향을 미치게 됩니다.
  24. 마지막으로 삼각관계에 대해 살펴보았습니다. 삼각형을 통해 소셜 네트워크를 이해하는 것은 사회학에서 많이 사용되는 방법 중 하나로 삼각관계의 링크 형태의 비율을 통해 전체 네트워크의 패턴을 보게 됩니다. 또한 물리학에서는 모티프 분석 등으로 불리며 사용되기도 합니다. 이 연구에서는 4가지 종류의 성별 조합에 따라 수많은 삼각형의 동형 대응이 나타날 수 있기 때문에 fully connected triangle을 대상으로 어떤 성별의 조합이 두드러지게 나타는지에 대해 살펴보았습니다. 이를 통해 어떤 성별의 조합이 더 안정적인지를 살펴볼 수 있을 것입니다. 이것을 얻기 위해 친구관계 중 한번이라도 위스퍼를 주고받은 관계만을 대상으로 네트워크를 구성하였고, random 값에 비해서 얼마나 더 관계가 발생하였는지를 보았습니다. 이 그림은 그 값이 높은 순서대로 정렬한 결과입니다. 파란색은 남성 성별을 의미하며, 빨간색은 여성을 의미합니다. 원 내부의 색은 플레이어의 성별을, 외부의 색은 아바타의 성별을 의미하고 삼각형에 적힌 숫자는 젠더 스와퍼의 숫자를 나타냅니다. 결과를 보면, 아바타의 성별이 섞인 경우가 한 아바타로만 구성된 삼각형보다 더 선호되는 것을 볼수 있습니다. 이 경향성은 레벨 50 이상의 상위 사용자들에게서 더 뚜렷히 나타났습니다. 마지막으로 남성2/여성1로 구성된 삼각관계가 여성2/남성1로 구성된 삼각관계보다 더 많이 나타났으며 이는 실제 소셜네트워크 서비스에서 분석된 결과와도 같습니다. 그 이유와 이 패턴이 나오게된 이유는 정확히 알 수 없지만 이러한 패턴이 온라인 게임과 그리고 다른 서비스에 걸쳐 드러나고 있는 것은 흥미로운 사실입니다.
  25. 정리하자면, 게임 내 성별, 그리고 실제 성별은 모두 페어 관계에 영향을 미치고 있었습니다. 메시지를 보내는 등의 커뮤니케이션에서는 상대방 성별에게 더 많은 메시지를 보내게 되었고, 친구관계 형성은 이에 반해 실제 성별의 영향을 받았습니다. 삼각관계에 있어서도 젠더 스와핑은 영향을 미치고 있음을 관찰하였습니다.
  26. 마지막으로 이 연구의 결론에 대해 말씀드리겠습니다.
  27. 젠더 스와핑은 온라인 게임을 보기 위한 새로운 뷰를 제공합니다. 이것들은 다양항 게임 내 향동들과 네트워크 패턴을 이해하기 위한 실마리를 제공하고 있습니다. 또한 이 트렌드들은 실제 세상에서 관찰되는 것들과 유사한 트렌드들을 보이고 있습니다. 대표적으로 소셜 네트워크에서의 삼각관계를 들 수 있는데요. 이는 대규모 다중 사용자 온라인 게임에 인간 행동에 관한 연구들, 소셜 네트워크 분석 연구에 있어서 실제 세상을 잘 반영하는 좋은 플랫폼임을 보여주고 있습니다. 이 연구에서 보여지는 결과들은 그 결과로써도 의미 있지만 다양한 어플리케이션으로써도 사용될 수 있습니다. 대표적으로 인공지능에 의해 동작하는 봇 시스템등을 탐지하는데 사용할 수 있을 것입니다. 성별 관련 특징들의 통계값을 온라인과 오프라인 성별의 조합에 의해 구축해 놓는 다면, 아웃라이어 탐지 기법 등을 이용해 탐지하는데 도움을 줄 수 있을 것입니다. 또한 이와 유사한 방식으로 online identity fraud detection에 있어서도 성별이 한 클루가 될 수 있음을 보여주는 결과랄 할 수 있습니다.
  28. 이 연구의 한계점은 다음과 같습니다. 이 연구는 한 게임에 대해서만 수행되었기에 다른 게임에서도 같은 결과를 나타낸다고 보장할수가 없습니다. 즉 일반화의 어려움이 있습니다. 또한 전수 데이터를 이용하였지만 데이터가 대만 게임 사용자들에 한정되었기 때문에 그 자체로써 샘플 바이어스가 존재합니다. 물론 이 점은 이후 행동과 네트워크 패턴에 있어서의 문화차이 연구 등에 사용될 수 있을 것입니다.
  29. 향후 연구로써는 다른 게임 데이터를 대상으로 한 유사한 분석을 통한 젠더스와핑에 대한 이해를 높일 수 있을 것이구요. 언어 사용패턴의 추가 분석을 통해 어떤 성역할을 따르는지를 더 엄밀히 검증할 수 있을 것으로 기대합니다. 또한 다른 온라인 서비스에서 행동과 네트워크 패턴이 오프라인에서의 그것들과는 어떻게 달라질 수 있는지를 이해할 수 있을 것입니다.
  30. 이 연구는 올해에 있었던 WWW컨퍼런스와 WIN workshop에서 발표된 연구에 기반하고 있으며 이 외에도 소셜 미디어에 관한 다른 연구들에도 전반적으로 관심을 가지고 연구를 진행하고 발표하였습니다.
  31. 지금까지 제 발표를 들어주셔서 감사합니다!
  32. 이어서 사람들의 사는 지역을 분석하였습니다. 대부분이 도시 지역에 사는 사용자들이었으나 31.25% 의 상당수 사용자들은 시골 지역에서 게임을 플레이하였습니다. 지역별 성비는 전체 지역에 걸쳐 일관되게 분포하고 있엇습니다.
  33. 첫째로 지역에 따른 상관관계를 분석하였습니다. 도시 지역에 사는 사람은, 성별 교체 현상에 보다 참여하였을까요? 어쩌면 직관적인 결과이겠지만 사는 지역은 성별 교체 현상을 참여하는 것과 통계적으로 유의미하게 관계가 없었습니다.