11 research outputs found
An Empirical Examination of an Online Game
ํ์๋
ผ๋ฌธ(๋ฐ์ฌ) -- ์์ธ๋ํ๊ต๋ํ์ : ๊ฒฝ์๋ํ ๊ฒฝ์ํ๊ณผ, 2022. 8. ์ก์ธ์ฑ.We propose a dynamic structural model of rational addiction to elucidate consumer behavior for online game consumption. Particularly, we propose a revised and extended utility model for rational addiction, by introducing the tedium factor based on a two-factor model of addiction. We demonstrate that the proposed model adequately explains consumer behavior in online gaming, particularly in modeling consumption reduction and churn patterns that cannot be explained by the existing rational addiction model. Moreover, we perform counterfactual simulations related to tedium and level-up difficulties, which affect consumption decisions and quantities as expected. Related discussion and implications are also provided.๋ณธ ์ฐ๊ตฌ๋ ์จ๋ผ์ธ ๊ฒ์ ์๋น ํ๋์ ์ค๋ช
ํ๊ธฐ ์ํด Becker and Murphy (1988)๊ฐ ์ ์ํ ํฉ๋ฆฌ์ ์ค๋
๋ชจํ์ ํ ๋๋ก ํ ๊ตฌ์กฐ์ ๋ํ ๋ชจํ์ ์ ์ํ๋ค. ํฉ๋ฆฌ์ ์ค๋
๋ชจํ์ ์จ๋ผ์ธ ๊ฒ์ ์๋น์์ ๋น๋ฒํ๊ฒ ๋ํ๋๋ ๊ณผ๋ํ ์๋น, ํน์ ์ค๋
์ ์ธ ์๋น ํ์์ ์ค๋ช
ํ๊ธฐ ์ํ์ฌ ์ ์๋ ๊ฒฝ์ ํ์ ๋ชจํ์ผ๋ก์, โ์ฌ์ฉ์ ์ํ ํ์ต (learning by doing)โ์ ๊ทผ๊ฑฐ๋ก ํ์ฌ ๊ณผ๊ฑฐ ์๋น ํจํด์ ํตํด ์ค๋
์์ค์ ์ธก์ , ์๋น์์ ์ค๋
์ ์ธ ์๋น ํ์๋ฅผ ๋ชจํํํ์๋ค. ๊ทธ๋ฌ๋ ๋ณธ ์ฐ๊ตฌ๋ ์ด๋ฌํ ๊ธฐ์กด ๋ชจํ์ด ์ค๋
์ ์ธ ์๋น๋ ์ค๋ช
ํ ์ ์์ผ๋, ์๋น์ ๊ฐ์ ๋๋ ์ดํ ํ์๋ฅผ ์ ์ ํ๊ฒ ๋ชจํํํ ์ ์๋ค๋ ์ฌ์ค์ ์ฐฉ์ํ์ฌ ๊ธฐ์กด์ ๋ชจํ์ ์์ โ ํ์ฅํ๊ณ ์ ํ์๋ค. ๊ตฌ์ฒด์ ์ผ๋ก, Berylne (1970) ๋ฑ ์ฌ๋ฆฌํ ๋ฌธํ์์ ์ค๋
์ ์ฃผ์ ์์๋ก์ ์ ์ํ ๊ถํ(tedium)๋ผ๋ ์๋ก์ด ์์๋ฅผ ๊ธฐ์กด ๋ชจํ์ ์ถ๊ฐํ์๋ค. ์๋น์๊ฐ ๊ฐ์ ์๊ทน์ ์ผ์ ์์ค ์ด์์ผ๋ก ๋ฐ๋ณต ๋
ธ์ถ๋ ๊ฒฝ์ฐ ์ค๋
์ ์ ๋๋ฅผ ์์ํ๋ ์์๋ก์ ๊ถํ๊ฐ ๋ฐ์ โ ๋์ ๋์ด, ๊ฒฐ๊ณผ์ ์ผ๋ก ์๋น๋์๋ ์ํฅ์ ๋ฏธ์น ์ ์๋ค๋ ๊ฒ์ด๋ค.
๋ณธ ์ฐ๊ตฌ๋ ์๋ฎฌ๋ ์ด์
์ ํตํด ๋ณธ ๋ชจํ์ด ์จ๋ผ์ธ ๊ฒ์ ์๋น ํ์์ ์ฆ๊ฐ ํ์์ ์ ๋๋ก ํฌ์ฐฉํ ์ ์๋ค๋ ์ฌ์ค์ ํ์ธํ๊ณ , ์ํ ๋ณ์์ ๊ฐ์น ํจ์๋ฅผ ํฌํจํ ๊ตฌ์กฐ์ ๋ํ ๋ชจํ์ ์ ์ํ์๋ค. ๊ทธ๋ฆฌ๊ณ ์จ๋ผ์ธ ๊ฒ์์ ์ค์ ์ฌ์ฉ์ ๋ ๋ฒจ ๋ก๊ทธ ๋ฐ์ดํฐ๋ฅผ ์ด์ฉํด ๋ชจํ์ ์ถ์ ํ์๋ค. ๊ทธ ๊ฒฐ๊ณผ, ์๋น์์ ์ค๋
์์ค์ด ํ์ฌ ์๋น๋ฅผ ์ฆ๊ฐ์ํค๋ ๋ฐ๋ฉด, ์๋น์์ ๊ถํ ์์ค์ ํ์ฌ ์๋น๋ฅผ ๊ฐ์์ํค๋ ๊ฒฝํฅ์ ๋ฐ๊ฒฌํ์๋ค. ๊ตฌ์กฐ์ ๋ํ ๋ชจํ์ ์ถ์ ๊ฒฐ๊ณผ๋ฅผ ๋ฐํ์ผ๋ก ํ ์ ์ฑ
์๋ฎฌ๋ ์ด์
๊ฒฐ๊ณผ ๋ํ ์ ์ํ์๋ค.
๋ณธ ์ฐ๊ตฌ๋ ๋ค์๊ณผ ๊ฐ์ ์ด๋ก ์ โ ์ค๋ฌด์ ์์ฌ์ ์ ๊ฐ์ง๋ค. ์ฒซ์งธ, ๊ธฐ์กด์ ํฉ๋ฆฌ์ ์ค๋
๋ชจํ์ ๊ถํ๋ผ๋ ์๋ก์ด ์์๋ฅผ ์ถ๊ฐํ ์์ โ ํ์ฅ ๋ชจํ์ ์ ์ํ์ฌ ๊ธฐ์กด์ ๋ชจํ์ด ์ค๋ช
ํ๊ธฐ ์ด๋ ค์ ๋ ์ค๋
์ ์๋น์์์ ๊ฐ์ ๋๋ ์ดํ ํ์์ ๊ณ๋์ ์ผ๋ก ๋ชจํํํ ์ ์๋ ์ ๊ทผ๋ฒ์ ์ ์ํ์๋ค. ๋์งธ, Berylne (1970)์ ์ค๋
๋ชจํ์ ๊ณ๋์ ์ผ๋ก ๋ถ์ํ ์ ์๋ ํ์ ์ ๊ณตํจ์ผ๋ก์จ ๋ธ๋๋ ์ ํ ๋ฌธํ์ด๋ ๊ด๊ณ ๋ฐ ์ ํ ๋์์ธ์ ํจ๊ณผ์ ๋ํ ๋ฌธํ ๋ฑ ํด๋น ๋ชจํ์ ํ์ฉํด์๋ ๋ง์ผํ
โ ๊ฒฝ์ํ ๋ฌธํ๋ค์ ์ด๋ก ์ ์ผ๋ก ๊ธฐ์ฌํ ๊ฒ์ผ๋ก ๊ธฐ๋ํ๋ค. ์
์งธ, ๋ณธ ์ฐ๊ตฌ์ ๊ฒฐ๊ณผ๊ฐ ์จ๋ผ์ธ ๊ฒ์ ์๋น ํ์์ ๋ํ ์ดํด์ ํต์ฐฐ์ ์ ๊ณตํ ๊ฒ์ผ๋ก ๊ธฐ๋ํ๋ค. ํนํ, ์ ํ ์ฐ๊ตฌ๊ฐ ๊ฒ์ ์๋น์ ์์ด ์ค๋
๋ฑ์ ์น์คํ์ฌ ์งํ๋์ด ์จ ๊ฒ์ ๋ฐํด, ๋ณธ ์ฐ๊ตฌ๋ ๊ฒ์์ ์ค๋
์ ์๋น์ ์์ด ๊ถํ๋ฅผ ์ฃผ์ํ ์์๋ก ๊ณ ๋ คํด์ผ ํ๋ค๋ ์ด๋ก ์ ๊ทผ๊ฑฐ๋ฅผ ์ ๊ณตํ๋ค. ๋ท์งธ, ๋ณธ ์ฐ๊ตฌ๋ ์ฒญ์๋
๋ฑ์ ๊ฒ์ ์ค๋
์ด ์ฌ๊ฐํ ์ฌํ ๋ฌธ์ ๋ก ๋๋๋๊ณ ์๋ ์ํฉ์์ ์ด๋ฅผ ๊ธฐ์
๊ณผ ์ ๋ถ ์
์ฅ์์ ๋ค์ํ ์ ์ฑ
์ ํตํด ๊ด๋ฆฌํ ์ ์๋ ์ด๋ก ์ ๊ธฐ๋ฐ์ ์ ๊ณตํ๋ค.Chapter 1. Introduction 1
Chapter 2. Literature Review 4
2.1. Online Game Consumption Behavior 4
2.2. Rational Addiction Model 6
2.3. Tedium 8
Chapter 3. Data and Model-free Analysis 13
3.1. Data 13
3.2. Model-free Analysis 14
Chapter 4. Model 19
4.1. Utility Model 20
4.2. The Law of Motion 23
4.2.1. Addiction 23
4.2.2. Level 24
4.2.3. Tedium 28
4.2.4. State Evolution 29
4.3. Dynamic Decision Problem 30
Chapter 5. Estimation 33
5.1. Estimations Strategy and Results 33
5.2. Identification Strategy 35
5.3. Policy Intervention 36
Chapter 6. Conclusion 39
References 43
Abstract in Korean 48๋ฐ
MMORPG์ ๊ฒ์ด๋จธ ๋คํธ์ํฌ ์งํ ๋ถ์
ํ์๋
ผ๋ฌธ (์์ฌ)-- ์์ธ๋ํ๊ต ๋ํ์ : ์ธ๋ก ์ ๋ณดํ๊ณผ, 2014. 2. ์ด์ฌํ.๋ณธ ์ฐ๊ตฌ๋ ์จ๋ผ์ธ ๊ฒ์์์ ๊ฒ์ด๋จธ ์ฌ์ด์ ์ํธ์์ฉ์ด ๊ฒ์์ ์ค์ฌ์ ๋์ด๊ณ , ์ํธ์์ฉ๊ณผ ์ํธ์์ฉ์ ๊ฒฐ๊ณผ ์์ฒด๊ฐ ์จ๋ผ์ธ ๊ฒ์์ ๋ด์ฉ์ด ๋๋ค๋ ์ ์ ํ์, World of Warcraft(WoW)๋ผ๋ MMORPG์ ๊ฒ์ด๋จธ๋ค ์ฌ์ด์์ ์ผ์ด๋๋ ์ํธ์์ฉ์ ํน์ง๊ณผ ์๊ฐ์ ๋ฐ๋ฅธ ์ํธ์์ฉ์ ๋ณํ ์์์ ๋ถ์ํ๊ณ ์ ํ๋ค.
์ด๋ฅผ ์ํด ์ํํธ์จ์ด ์ฐ๊ตฌ(software studies), MMORPG์์์ ์ํธ์์ฉ์ฑ, ๋คํธ์ํฌ ๊ณผํ(network science)์ ์ด๋ก ์ ๊ธฐ๋ฐ์ผ๋ก ์ผ์๋ค. ์ํํธ์จ์ด ์ฐ๊ตฌ๋ ์ํธ์์ฉ์ ํ๊ฒฝ์ด ๋๋ ์ํํธ์จ์ด์ ๋ํ ์ดํด๋ฅผ ๋ฐํ์ผ๋ก ๊ฒ์ด๋จธ์ ์ํธ์์ฉ์ ๋ถ์ํด์ผ ํ๋ค๋ ์ ์ ์ ์ํ๋ค. MMORPG์์์ ์ํธ์์ฉ์ฑ๊ณผ ๊ด๋ จ๋ ์ด๋ก ์ ์ํธ์์ฉ์ ๋ถ์์์ค์ ๊ฒ์ด๋จธ(์๋ฐํ), ๊ฒ์ด๋จธ ์ง๋จ(๊ธธ๋), ๊ฒ์ด๋จธ ์ ์ฒด์ 3๊ฐ ์์ค์ผ๋ก ๊ตฌ๋ถํ๋ ๋ฐฐ๊ฒฝ์ด ๋์๋ค. ๋คํธ์ํฌ ๊ณผํ์ ํตํด์๋ ๊ฒ์ด๋จธ๋ค์ ์ํธ์์ฉ์ผ๋ก ์ฐ๊ฒฐ๋ ํ๋์ ๋คํธ์ํฌ๋ก ๊ฐ์ฃผํจ์ผ๋ก์จ ์ฌํ์ฐ๊ฒฐ๋ง๋ถ์(SNA) ๊ธฐ๋ฒ์ ๊ฐ์ข
์งํ๋ฅผ ํ์ฉํ ์ ์์์ ๋ฟ๋ง ์๋๋ผ, ์ํธ์์ฉ ๋คํธ์ํฌ๊ฐ ์๊ฐ์ ๋ฐ๋ผ ๋ณํํ๋ค๋ ์งํ ๋คํธ์ํฌ(evolving network)์ ๊ด์ ์ ์ ์ฉํ ์ ์์๋ค.
๋ถ์ ๋์์ ํฌ๋กค๋ง ๋ฐฉ์์ผ๋ก WoW์ 1๊ฐ ๋๋ง ์๋ฒ์์ 3๋
๊ฐ ์์ง๋ WoWAH๋ผ๋ ๊ณต๊ฐ ๋ฐ์ดํฐ์๋ค. ์ด ์ค 2006๋
1์ 6์ผ~2007๋
1์ 5์ผ์ ์์ง๋ 1๋
๊ฐ์ ๋ฐ์ดํฐ๋ฅผ 52๊ฐ์ ์ฃผ์ฐจ๋ณ ๋ฐ์ดํฐ๋ก ๊ตฌ๋ถํ๊ณ , 3๊ฐ ๋ถ์์์ค๋ณ๋ก ์์ฑ ์งํ์ ์ํธ์์ฉ ์งํ๋ฅผ ๋์ถํ์๋ค. ์ด ๊ณผ์ ์์ ๊ฒ์ด๋จธ ๊ฐ์ ์ํธ์์ฉ์ ์๋ฐํ๊ฐ ํ(ํํฐ)์ ๊ตฌ์ฑํด ๊ฒ์ ํ๋ ์ด์ ์ฐธ์ฌํ๋ ํ์๋ก ์ ์๋์๋ค. ์ด 52์ฃผ์ ๊ฑธ์ณ ๋ถ์์์ค๋ณ ์์ฑ, ์ํธ์์ฉ ์งํ๋ค์ ๋ณํ๋ฅผ ๊ด์ฐฐํ์์ผ๋ฉฐ, t ์์ ์ ์์ฑ ์งํ์ t+1 ์์ ์ ์ํธ์์ฉ ์งํ ๊ฐ์ ์๊ด๊ด๊ณ๋ ๊ฒํ ํ์๋ค. ์ด ๊ธฐ๊ฐ ์ค ๊ด์ฐฐ๋ ์๋ฐํ๋ 28,267 ๊ฐ, ๊ธธ๋๋ 154๊ฐ์์ผ๋ฉฐ, ์๋ฐํ์ ํ๊ท ์กด์๊ธฐ๊ฐ์ 5.463์ฃผ, ๊ธธ๋์ ํ๊ท ์กด์๊ธฐ๊ฐ์ 16.85์ฃผ์๋ค.
[์ฐ๊ตฌ๋ฌธ์ 1]์ ๊ฐ๋ณ ๊ฒ์ด๋จธ ์์ค์ ์์ฑ, ์ํธ์์ฉ ์งํ๋ ์๊ฐ์ ๋ฐ๋ผ ์ด๋ป๊ฒ ๋ณํํ๋๊ฐ?์๋ค. ๊ฒ์ด๋จธ ์์ค์ ์์ฑ ์งํ๋ก๋ ์๋ฐํ์ ๋ ๋ฒจ๊ณผ ํ๋ ์ด ์๊ฐ์, ์ํธ์์ฉ ์งํ๋ก๋ ์ํธ์์ฉ ์๊ฐ, ์ํธ์์ฉ ํ์์ ํจ๊ป ์ฐ๊ฒฐ์ ๋์ค์ฌ์ฑ, ๋งค๊ฐ์ค์ฌ์ฑ, ๊ทผ์ ์ค์ฌ์ฑ์ 3๊ฐ ์ค์ฌ์ฑ ์งํ๋ฅผ ์ ์ ํ์๋ค.
[์ฐ๊ตฌ๋ฌธ์ 2]๋๊ฒ์ด๋จธ ์ง๋จ ์์ค์ ์์ฑ, ์ํธ์์ฉ ์งํ๋ ์๊ฐ์ ๋ฐ๋ผ ์ด๋ป๊ฒ ๋ณํํ๋๊ฐ?์๋ค. ๊ฒ์ด๋จธ ์ง๋จ์ ๊ฐ๋
์ ๊ธธ๋๋ก ํ์ ํ๊ณ ๊ธธ๋์ ์์ฑ ์งํ๋ก๋ ํฌ๊ธฐ, ์์ ์๋ฐํ์ ํ๊ท ๋ ๋ฒจ, ์์ ์๋ฐํ์ ํ๊ท ํ๋ ์ด ์๊ฐ์ ์ ์ ํ์๋ค. ์ํธ์์ฉ ์งํ๋ก๋ ํ๊ท ์ํธ์์ฉ ์๊ฐ, ํ๊ท ์ํธ์์ฉ ํ์, ๋ฐ๋, E-I ์งํ์ 4๊ฐ๋ฅผ ์ ์ ํ์๋ค.
[์ฐ๊ตฌ๋ฌธ์ 3]์ ์ ์ฒด ๊ฒ์ด๋จธ ๋คํธ์ํฌ ์์ค์ ์์ฑ, ์ํธ์์ฉ ์งํ๋ ์๊ฐ์ ๋ฐ๋ผ ์ด๋ป๊ฒ ๋ณํํ๋๊ฐ?์๋ค. ์ ์ฒด ๋คํธ์ํฌ ์์ค์ ์์ฑ ์งํ๋ก๋ ํฌ๊ธฐ, ๊ธธ๋ ์, ์ ์ฒด ํ๋ ์ด ์๊ฐ์ 3๊ฐ๊ฐ ์ ์ ๋์์ผ๋ฉฐ, ์ํธ์์ฉ ์งํ๋ก๋ ์ํธ์์ฉ ์๊ฐ ํฉ๊ณ, ์ํธ์์ฉ ํ์ ํฉ๊ณ, ๋ฐ๋, ์ง๊ฒฝ, ํฌ๊ด์ฑ, ์ง์ค๋, ํ๊ท ์ฐ๊ฒฐ๊ฑฐ๋ฆฌ, ๊ตฐ์งํ ๊ณ์์ 8๊ฐ๋ฅผ ์ ์ ํ์๋ค.
๊ฐ ์ฐ๊ตฌ๋ฌธ์ ์ ๋ํ ๊ตฌ์ฒด์ ์ธ ๋ถ์์ ์ข
ํฉํ ๊ฒฐ๊ณผ๋ ๋ค์๊ณผ ๊ฐ๋ค.
์ฒซ์งธ, ์๋ฐํ, ๊ธธ๋, ์ ์ฒด ๋คํธ์ํฌ ์์ค ์ ๋ฐ์์ ์์ฑ ์งํ๋ ๊ฐ์ํ๋ ์์ค์๋ ์ํธ์์ฉ ์งํ๋ ๋์ฒด๋ก ์ ์ง๋๋ ๊ฒฝํฅ์ด ํ์ธ๋์๋ค. WoW ์๋ฐํ ๊ฐ ์ํธ์์ฉ์ ๋คํธ์ํฌ๋ ์์ฑ ์งํ์ ์ง์์ ์ธ ๋ณํ์๋ ๋ถ๊ตฌํ๊ณ ์ํธ์์ฉ ์ธก๋ฉด์ ํญ์์ฑ์ ์ ์งํ๋ ๊ฒ์ผ๋ก ๋ณด์ธ๋ค.
๋์งธ, ๊ฒ์ ๋ด ๋ํ ์ด๋ฒคํธ์ ์ผ์์ ์ด๊ณ ์ ํ์ ์ธ ์ํธ์์ฉ ์ฆ๋ ํจ๊ณผ๊ฐ ๋ฐ๊ฒฌ๋์๋ค. 3๊ฐ ๋ถ์์์ค์์ ๋ํ ์ด๋ฒคํธ๊ฐ ๋ฒ์ด์ง 35์ฃผ์ฐจ๋ฅผ ๊ธฐ์ ์ผ๋ก ๋ค์์ ์ํธ์์ฉ ์งํ๊ฐ 5~6์ฃผ๊ฐ ์ผ์์ ์ผ๋ก ๊ธ๊ฒฉํ ์ฆ๊ฐํ๋ค๊ฐ ๋ค์ ๊ฐ์ํ๋ ํ์์ด ๊ด์ฐฐ๋์๋ค. ๋ํ ๋ํ ์ด๋ฒคํธ๋ก ์ธํ ์ํธ์์ฉ ์ฆ๋ ํจ๊ณผ๋ ์ผ๋ถ ์๋ฐํ๋ค์๊ฒ์๋ง ๋ํ๋๋ ๊ฒ์ผ๋ก ๋ถ์๋์๋ค.
์
์งธ, ๊ธธ๋๊ฐ ๋ฐ๋์ ์์ ์๋ฐํ ๊ฐ์ ์ํธ์์ฉ์ด๋ ํ๋ ์ด ์๊ฐ์ ๋๋ฆฌ๋ ๊ฒ์ ์๋๋ผ๋ ์ ์ด ๋ฐ๊ฒฌ๋์๋ค. ๊ธธ๋ ์์ ์๋ฐํ๋ค์ ํ๊ท ํ๋ ์ด ์๊ฐ์ด ์ ์ฒด ์๋ฐํ์ ๊ฒฝ์ฐ๋ณด๋ค ๋ ๋น ๋ฅด๊ฒ ์ค์ด๋ค๊ณ ์์์ผ๋ฉฐ, E-I ์งํ๋ฅผ ํตํด ๊ธธ๋ ์์ ์๋ฐํ๋ค์ด ๊ธธ๋ ์ธ๋ถ์ ์๋ฐํ๋ค๊ณผ ๋ ๋ง์ด ์ํธ์์ฉํ๊ณ ์๋ค๋ ์ ์ ํ์ธํ ์ ์์๋ค.
๋ท์งธ, ํฌ๊ธฐ์ ์์ ์๋ฐํ๋ค์ ํ๊ท ๋ ๋ฒจ์ ๊ธฐ์ค์ผ๋ก ๊ด์ฐฐ๋ ๋ชจ๋ ๊ธธ๋๋ค์ ์ ๊ท(New), ์ด๋ณด์(Newbie), ์๊ท๋ชจ(Small), ์๋ฆฌํธ(Elite), ๋ํ(Big), ๋ถ์์ (Unstable)์ 6๊ฐ ์ ํ์ผ๋ก ๊ตฌ๋ถํ๊ณ , ๊ฐ ์ ํ๋ง๋ค ์ํธ์์ฉ ์งํ์ ์ฐจ์ด๊ฐ ์๋ค๋ ์ ์ ํ์ธํ์๋ค. ์๋ฅผ ๋ค์ด ๋ํ ๊ธธ๋๋ ํ๊ท ์ํธ์์ฉ ์๊ฐ๊ณผ ํ๊ท ์ํธ์์ฉ ํ์๊ฐ ๋ค๋ฅธ ์ ํ์ ๊ธธ๋๋ณด๋ค ์๋ฑํ ์ปธ์ผ๋ฉฐ, E-I ์งํ๋ ๋ค๋ฅธ ์ ํ์ ๊ธธ๋๋ณด๋ค ํ์ ํ ์์๋ค. ์๋ฆฌํธ ๊ธธ๋๋ ํ๊ท ์ํธ์์ฉ ์๊ฐ๊ณผ ์ํธ์์ฉ ํ์๊ฐ ๋ค๋ฅธ ์ ํ์ ๊ธธ๋๋ณด๋ค ๋งค์ฐ ์ ์์ผ๋ฉฐ, ์๊ท๋ชจ ๊ธธ๋์ ๋ถ์์ ๊ธธ๋๋ ๋ค๋ฅธ ์ ํ๋ณด๋ค E-I ์งํ๊ฐ ์๋ฑํ ๋์๋ค.
๋ค์ฏ์งธ, WoW์ ๊ฒ์ ํ๋ ์ด์์ ์๋ฐํ ๊ฐ ์ํธ์์ฉ์ด ์ ๋์ ์ธ ๋น์ค์ ์ฐจ์งํ๋ ๊ฒ์ ์๋์ง๋ง, ์๋ฐํ์ ๋คํธ์ํฌ ์ดํ์ ๋ง๋ ํจ๊ณผ๊ฐ ์๋ค๋ ๊ฒ์ด ํ์ธ๋์๋ค. WoW์์ ์ํธ์์ฉ์ ํตํด ์ฐ๊ฒฐ๋ ์๋ฐํ์ ์๋ ์ ์ฒด ์๋ฐํ์ 20% ๊ฐ๋์ ๋ถ๊ณผํ๋ค. ์ด๋ WoW์์ ์ํธ์์ฉ์ด ๊ฒ์ ์งํ์ ํ์๋ถ๊ฐ๊ฒฐ ์์๋ ์๋ ์ ์๋ค๋ ๋ป์ด๋ค. ๊ทธ๋ฌ๋ 1~52์ฃผ์ฐจ์ ๊ฑธ์ณ ์ ์ฒด ๋คํธ์ํฌ์ ํฌ๊ธฐ๊ฐ ์ค์ด๋๋ ๊ฐ์ด๋ฐ ์ํธ์์ฉ์ ํตํด ์ฐ๊ฒฐ๋ ์๋ฐํ์ ์๋ ์ผ์ ์์ค์ผ๋ก ์ ์ง๋์๋ค. ์ด๋ ๋คํธ์ํฌ์์ ์ดํํ๋ ์๋ฐํ๋ ์ฃผ๋ก ๋ค๋ฅธ ์๋ฐํ๋ค๊ณผ ์ํธ์์ฉ์ ํ์ง ์๋ ๊ณ ๋ฆฝ๋ ์๋ฐํ๋ค์ด๋ผ๋ ๊ฒ์ ๋ํ๋ธ๋ค,
์ฌ์ฏ์งธ, ์๋ฐํ์ ์ํธ์์ฉ ๋คํธ์ํฌ๊ฐ ์์ ์ธ๊ณ ๋คํธ์ํฌ(Small-World network)๋ผ๋ ์ ์ด ํ์ธ๋์๋ค. ์๋ฐํ ๊ฐ ์ํธ์์ฉ์ ๋คํธ์ํฌ๋ ๊ตฐ์งํ ๊ณ์๊ฐ ๋ฌด์์ ๋คํธ์ํฌ๋ณด๋ค ์๋ฐฑ ๋ฐฐ ์ด์ ํฐ, ๋งค์ฐ ์์ ์ธ๊ณ๋ฅผ ํ์ฑํ๊ณ ์์๋ค. ์ด๋ ๋ค๋ฅธ ์๋ฐํ๋ค๋ณด๋ค ์๋ฑํ ์ฐ๊ฒฐ์ ์๊ฐ ๋ง์ ์์์ ํ๋ธ ์๋ฐํ๋ค ๋๋ฌธ์ด๋ค. ์ด๋ฅผ ํตํด ์์ ์ธ๊ณ ๋คํธ์ํฌ๊ฐ MMORPG๋ผ๋ ๊ฐ์ ์ธ๊ณ์ ์ฐ๊ฒฐ๋ง์์๋ ๋ํ๋๋ ๋ณดํธ์ ํ์์ด๋ผ๋ ์ ์ ์ฌํ์ธํ์๋ค.
๋ณธ ์ฐ๊ตฌ์ ์์๋ ๋ค์๊ณผ ๊ฐ๋ค. ์ฒซ์งธ, ๊ฒ์ด๋จธ์ ์ํธ์์ฉ์ ํน์ ์์ ์์๋ง ๋ถ์ํ์ง ์๊ณ ์๊ฐ์ ํ๋ฆ์ ๋ฐ๋ฅธ ์ํธ์์ฉ์ ๋ณํ ์์์ ์ถ์ ํ์์ผ๋ฉฐ, ๊ฒ์ด๋จธ, ๊ฒ์ด๋จธ ์ง๋จ, ์ ์ฒด ๋คํธ์ํฌ์ ์ธ ๋ถ์์์ค์ ๋ณตํฉ์ ์ผ๋ก ๊ณ ๋ คํ์๋ค. ๋์งธ, MMORPG์์ ํฌ๋กค๋ง๋ ๋๊ท๋ชจ ๋ฐ์ดํฐ์์ ์ํธ์์ฉ ์ ๋ณด๋ฅผ ์ถ์ถํ๋ ๋ฐฉ๋ฒ๊ณผ ์๋ฒ ์ ๊ฒ ๊ธฐ๊ฐ์ ๊ธฐ์ค์ผ๋ก ์๊ฐ ๋จ์๋ฅผ ๊ตฌ๋ถํด ์๊ณ์ด ๋ถ์์ ์ ์ฉํ๋ ๋ฐฉ๋ฒ์ ์ ์ํ์๋ค. ์
์งธ, ๊ฒ์ ๊ฐ๋ฐ์ฌ๋ ์ด์์ฌ๋ ๊ฒ์ด๋จธ์ ์ํธ์์ฉ์ ์ฆ์ง์ํค๊ธฐ ์ํด ์๋ฒ ํตํฉ์ด๋ ๋ํ ์ด๋ฒคํธ ์ด์ธ์ ์๋จ์ ๊ฐ๊ตฌํด์ผ ํ๋ค๋ ์ค์ง์ ์กฐ์ธ์ ์ ์ํ์๋ค.์ 1์ฅ ๋ฌธ์ ์ ์ ๊ธฐ
์ 2์ฅ ๋ค์ค์ ์์จ๋ผ์ธ๊ฒ์(MMORPG)
์ 1์ ์จ๋ผ์ธ ๊ฒ์์ ์ ์
์ 2์ MMORPG์ ์ ์
์ 3์ MMORPG์ ์ ํ๊ณผ ์ฌ๋ก
์ 3์ฅ ์ ํ์ฐ๊ตฌ ๊ฒํ
์ 1์ MMORPG ๊ฒ์ด๋จธ์ ์ํธ์์ฉ์ ๋ํ ์ฐ๊ตฌ
์ 2์ ๊ฒ์์์ ์ถ์ถ๋ ๋ฐ์ดํฐ๋ฅผ ์ฌ์ฉํ MMORPG ์ํธ์์ฉ ์ฐ๊ตฌ
์ 3์ ์ ํ์ฐ๊ตฌ์ ํน์ง๊ณผ ํ๊ณ
์ 4์ฅ ์ด๋ก ์ ๋ฐฐ๊ฒฝ
์ 1์ ์ํํธ์จ์ด ์ฐ๊ตฌ
์ 2์ MMORPG ๊ฒ์ด๋จธ ์ํธ์์ฉ
์ 3์ MMORPG์์์ ๋คํธ์ํฌ
์ 5์ฅ ์ฐ๊ตฌ๋ฌธ์
์ 1์ ๋ถ์ํ(Model)
์ 2์ ์ฐ๊ตฌ๋ฌธ์
์ 3์ ์ฃผ์ ์ ์ด์ ์ ๋ฆฌ
1. ์ํธ์์ฉ
2. ๊ฐ๋ณ ๊ฒ์ด๋จธ
3. ๊ฒ์ด๋จธ ์ง๋จ
4. ์ ์ฒด ๊ฒ์ด๋จธ ๋คํธ์ํฌ
์ 6์ฅ ์ฐ๊ตฌ ๋ฐฉ๋ฒ
์ 1์ ์ฐ๊ตฌ๋์
์ 2์ ์๋ฃ์์ง
์ 3์ ๋ถ์๋ฐฉ๋ฒ
1. ์ํธ์์ฉ ๋ฐ์ดํฐ์ ์ถ์ถ
2. ๋ฐ์ดํฐ์ ์๊ฐ ๊ตฌ๋ถ
์ 4์ ์ง์ํ
1. ์ํธ์์ฉ
2. ๊ฐ๋ณ ๊ฒ์ด๋จธ
3. ๊ฒ์ด๋จธ ์ง๋จ
4. ์ ์ฒด ๊ฒ์ด๋จธ ๋คํธ์ํฌ
์ 7์ฅ ์ฐ๊ตฌ ๊ฒฐ๊ณผ
์ 1์ ๊ฐ๊ด
1. ์ ์ฒด ์๋ฐํ ์ ๋ฐ ์ข
์กฑ, ์ง์
๋ณ ๋ถํฌ, ์กด์๊ธฐ๊ฐ
2. ์ ์ฒด ๊ธธ๋ ์ ๋ฐ ์กด์๊ธฐ๊ฐ
์ 2์ ๊ฐ๋ณ ์๋ฐํ ์์ค: ์ฐ๊ตฌ๋ฌธ์ 1
1. ์ฃผ๋ณ ์๋ฐํ ์์ฑ ์งํ ๋ณํ: ์ฐ๊ตฌ๋ฌธ์ 1-1
2. ์ฃผ๋ณ ์๋ฐํ ์ํธ์์ฉ ์งํ ๋ณํ: ์ฐ๊ตฌ๋ฌธ์ 1-2
3. ์๋ฐํ ์์ฑ ์งํ์ ์ํธ์์ฉ ์งํ ๊ฐ ๊ด๊ณ: ์ฐ๊ตฌ๋ฌธ์ 1-3
์ 3์ ์ง๋จ ์์ค: ์ฐ๊ตฌ๋ฌธ์ 2
1. ์ฃผ๋ณ ๊ธธ๋ ์์ฑ ์งํ ๋ณํ: ์ฐ๊ตฌ๋ฌธ์ 2-1
2. ์ฃผ๋ณ ๊ธธ๋ ์ํธ์์ฉ ์งํ ๋ณํ: ์ฐ๊ตฌ๋ฌธ์ 2-2
3. ๊ธธ๋ ์์ฑ ์งํ์ ๊ธธ๋ ์ํธ์์ฉ ์งํ ๊ฐ ๊ด๊ณ: ์ฐ๊ตฌ๋ฌธ์ 2-3
4. ์๊ฐ์ ๋ฐ๋ฅธ ๊ธธ๋ ์ ํ์ ๋ณํ
์ 4์ ์ ์ฒด ๋คํธ์ํฌ ์์ค: ์ฐ๊ตฌ๋ฌธ์ 3
1. ์ฃผ๋ณ ์ ์ฒด ๋คํธ์ํฌ ์์ฑ ์งํ ๋ณํ: ์ฐ๊ตฌ๋ฌธ์ 3-1
2. ์ฃผ๋ณ ์ ์ฒด ๋คํธ์ํฌ ์ํธ์์ฉ ์งํ ๋ณํ: ์ฐ๊ตฌ๋ฌธ์ 3-2
3. ์ ์ฒด ๋คํธ์ํฌ ์์ฑ ์งํ์ ์ํธ์์ฉ ์งํ ๊ฐ ๊ด๊ณ: ์ฐ๊ตฌ๋ฌธ์ 3-3
4. ์ ์ฒด ๋คํธ์ํฌ ์๊ฐํ
5. ์์ ์ธ๊ณ ํ์
์ 5์ ํด์ ๋ฐ ๋
ผ์
1. ์์ฝ
2. ํด์ ๋ฐ ๋
ผ์
์ 8์ฅ ๊ฒฐ๋ก : ์ฐ๊ตฌ์ ์์ ๋ฐ ํ๊ณ
์ฐธ๊ณ ๋ฌธํMaste
Analyzing the effect of tcp and server population on massively multiplayer games
Many Massively Multiplayer Online Role-Playing Games (MMORPGs) use TCP flows for communication between the server and the game clients. The utilization of TCP, which was not initially designed for (soft) real-time services, has many implications for the competing traffic flows. In this paper we present a series of studies which explore the competition between MMORPG and other traffic flows. For that aim, we first extend a source-based traffic model, based on playerโs activities during the day, to also incorporate the impact of the number of players sharing a server (server population) on network traffic. Based on real traffic traces, we statistically model the influence of the variation of the serverโs player population on the network traffic, depending on the action categories (i.e., types of in-game player behaviour). Using the developed traffic model we prove that while server population only modifies specific action categories, this effect is significant enough to be observed on the overall traffic. We find that TCP Vegas is a good option for competing flows in order not to throttle the MMORPG flows and that TCP SACK is more respectful with game flows than other TCP variants, namely, Tahoe, Reno, and New Reno. Other tests show that MMORPG flows do not significantly reduce their sending window size when competing against UDP flows. Additionally, we study the effect of RTT unfairness between MMORPG flows, showing that it is less important than in the case of network-limited TCP flows
Analyzing the Effect of TCP and Server Population on Massively Multiplayer Games
Many Massively Multiplayer Online Role-Playing Games (MMORPGs) use TCP flows for communication between the server and the game clients. The utilization of TCP, which was not initially designed for (soft) real-time services, has many implications for the competing traffic flows. In this paper we present a series of studies which explore the competition between MMORPG and other traffic flows. For that aim, we first extend a source-based traffic model, based on playerโs activities during the day, to also incorporate the impact of the number of players sharing a server (server population) on network traffic. Based on real traffic traces, we statistically model the influence of the variation of the serverโs player population on the network traffic, depending on the action categories (i.e., types of in-game player behaviour). Using the developed traffic model we prove that while server population only modifies specific action categories, this effect is significant enough to be observed on the overall traffic. We find that TCP Vegas is a good option for competing flows in order not to throttle the MMORPG flows and that TCP SACK is more respectful with game flows than other TCP variants, namely, Tahoe, Reno, and New Reno. Other tests show that MMORPG flows do not significantly reduce their sending window size when competing against UDP flows. Additionally, we study the effect of RTT unfairness between MMORPG flows, showing that it is less important than in the case of network-limited TCP flows
Enhancing trustability in MMOGs environments
Massively Multiplayer Online Games (MMOGs; e.g., World of Warcraft), virtual worlds
(VW; e.g., Second Life), social networks (e.g., Facebook) strongly demand for more
autonomic, security, and trust mechanisms in a way similar to humans do in the real
life world. As known, this is a difficult matter because trusting in humans and organizations
depends on the perception and experience of each individual, which is difficult to
quantify or measure. In fact, these societal environments lack trust mechanisms similar
to those involved in humans-to-human interactions. Besides, interactions mediated
by compute devices are constantly evolving, requiring trust mechanisms that keep the
pace with the developments and assess risk situations.
In VW/MMOGs, it is widely recognized that users develop trust relationships from their
in-world interactions with others. However, these trust relationships end up not being
represented in the data structures (or databases) of such virtual worlds, though they
sometimes appear associated to reputation and recommendation systems. In addition,
as far as we know, the user is not provided with a personal trust tool to sustain his/her
decision making while he/she interacts with other users in the virtual or game world.
In order to solve this problem, as well as those mentioned above, we propose herein a
formal representation of these personal trust relationships, which are based on avataravatar
interactions. The leading idea is to provide each avatar-impersonated player
with a personal trust tool that follows a distributed trust model, i.e., the trust data is
distributed over the societal network of a given VW/MMOG.
Representing, manipulating, and inferring trust from the user/player point of view certainly
is a grand challenge. When someone meets an unknown individual, the question
is โCan I trust him/her or not?โ. It is clear that this requires the user to have access to
a representation of trust about others, but, unless we are using an open source VW/MMOG,
it is difficult โnot to say unfeasibleโ to get access to such data. Even, in an open
source system, a number of users may refuse to pass information about its friends, acquaintances,
or others. Putting together its own data and gathered data obtained from
others, the avatar-impersonated player should be able to come across a trust result
about its current trustee. For the trust assessment method used in this thesis, we use
subjective logic operators and graph search algorithms to undertake such trust inference
about the trustee. The proposed trust inference system has been validated using
a number of OpenSimulator (opensimulator.org) scenarios, which showed an accuracy
increase in evaluating trustability of avatars.
Summing up, our proposal aims thus to introduce a trust theory for virtual worlds, its
trust assessment metrics (e.g., subjective logic) and trust discovery methods (e.g.,
graph search methods), on an individual basis, rather than based on usual centralized
reputation systems. In particular, and unlike other trust discovery methods, our methods
run at interactive rates.MMOGs (Massively Multiplayer Online Games, como por exemplo, World of Warcraft),
mundos virtuais (VW, como por exemplo, o Second Life) e redes sociais (como por exemplo,
Facebook) necessitam de mecanismos de confianรงa mais autรณnomos, capazes de
assegurar a seguranรงa e a confianรงa de uma forma semelhante ร que os seres humanos
utilizam na vida real. Como se sabe, esta nรฃo รฉ uma questรฃo fรกcil. Porque confiar em
seres humanos e ou organizaรงรตes depende da percepรงรฃo e da experiรชncia de cada indivรญduo,
o que รฉ difรญcil de quantificar ou medir ร partida. Na verdade, esses ambientes
sociais carecem dos mecanismos de confianรงa presentes em interacรงรตes humanas presenciais.
Alรฉm disso, as interacรงรตes mediadas por dispositivos computacionais estรฃo em
constante evoluรงรฃo, necessitando de mecanismos de confianรงa adequados ao ritmo da
evoluรงรฃo para avaliar situaรงรตes de risco.
Em VW/MMOGs, รฉ amplamente reconhecido que os utilizadores desenvolvem relaรงรตes
de confianรงa a partir das suas interacรงรตes no mundo com outros. No entanto, essas relaรงรตes
de confianรงa acabam por nรฃo ser representadas nas estruturas de dados (ou bases
de dados) do VW/MMOG especรญfico, embora ร s vezes apareรงam associados ร reputaรงรฃo
e a sistemas de reputaรงรฃo. Alรฉm disso, tanto quanto sabemos, ao utilizador nรฃo lhe
รฉ facultado nenhum mecanismo que suporte uma ferramenta de confianรงa individual
para sustentar o seu processo de tomada de decisรฃo, enquanto ele interage com outros
utilizadores no mundo virtual ou jogo. A fim de resolver este problema, bem como
os mencionados acima, propomos nesta tese uma representaรงรฃo formal para essas relaรงรตes
de confianรงa pessoal, baseada em interacรงรตes avatar-avatar. A ideia principal
รฉ fornecer a cada jogador representado por um avatar uma ferramenta de confianรงa
pessoal que segue um modelo de confianรงa distribuรญda, ou seja, os dados de confianรงa
sรฃo distribuรญdos atravรฉs da rede social de um determinado VW/MMOG.
Representar, manipular e inferir a confianรงa do ponto de utilizador/jogador, รฉ certamente
um grande desafio. Quando alguรฉm encontra um indivรญduo desconhecido, a
pergunta รฉ โPosso confiar ou nรฃo nele?โ. ร claro que isto requer que o utilizador tenha
acesso a uma representaรงรฃo de confianรงa sobre os outros, mas, a menos que possamos
usar uma plataforma VW/MMOG de cรณdigo aberto, รฉ difรญcil โ para nรฃo dizer impossรญvel
โ obter acesso aos dados gerados pelos utilizadores. Mesmo em sistemas de cรณdigo
aberto, um nรบmero de utilizadores pode recusar partilhar informaรงรตes sobre seus amigos,
conhecidos, ou sobre outros. Ao juntar seus prรณprios dados com os dados obtidos de
outros, o utilizador/jogador representado por um avatar deve ser capaz de produzir uma
avaliaรงรฃo de confianรงa sobre o utilizador/jogador com o qual se encontra a interagir.
Relativamente ao mรฉtodo de avaliaรงรฃo de confianรงa empregue nesta tese, utilizamos
lรณgica subjectiva para a representaรงรฃo da confianรงa, e tambรฉm operadores lรณgicos da
lรณgica subjectiva juntamente com algoritmos de procura em grafos para empreender
o processo de inferรชncia da confianรงa relativamente a outro utilizador. O sistema de
inferรชncia de confianรงa proposto foi validado atravรฉs de um nรบmero de cenรกrios Open-Simulator (opensimulator.org), que mostrou um aumento na precisรฃo na avaliaรงรฃo da
confianรงa de avatares.
Resumindo, a nossa proposta visa, assim, introduzir uma teoria de confianรงa para mundos
virtuais, conjuntamente com mรฉtricas de avaliaรงรฃo de confianรงa (por exemplo, a
lรณgica subjectiva) e em mรฉtodos de procura de caminhos de confianรงa (com por exemplo,
atravรฉs de mรฉtodos de pesquisa em grafos), partindo de uma base individual, em
vez de se basear em sistemas habituais de reputaรงรฃo centralizados. Em particular, e ao
contrรกrio de outros mรฉtodos de determinaรงรฃo do grau de confianรงa, os nossos mรฉtodos
sรฃo executados em tempo real
The internet of ontological things: On symmetries between ubiquitous problems and their computational solutions in the age of smart objects
This dissertation is about an abstract form of computer network that has recently earned a new physical incarnation called โthe Internet of Things.โ It surveys the ontological transformations that have occurred over recent decades to the computational components of this network, objectsโinitially designed as abstract algorithmic agents in a source code of computer programming but now transplanted into real-world objects. Embodying the ideal of modularity, objects have provided computer programmers with more intuitive means to construct a software application with lots of simple and reusable functional building blocks. Their capability of being reassembled into many different networks for a variety of applications has also embodied another ideal of computing machines, namely general-purposiveness. In the algorithmic cultures of the past century, these objects existed as mere abstractions to help humans to understand electromagnetic signals that had infiltrated every corner of automatized spaces from private to public. As an instrumental means to domesticate these elusive signals into programmable architectures according to the goals imposed by professional programmers and amateur end-users, objects promised a universal language for any computable human activities. This utopian vision for the object-oriented domestication of the digital has had enough traction for the growth of the software industry as it has provided an alibi to hide another process of colonization occurring on the flipside of their interfacing between humans and machines: making programmable the highest number of online and offline human activities possible. A more recent media age, which this dissertation calls the age of the Internet of Things, refers to the second phase of this colonization of human cultures by the algorithmic objects, no longer trapped in the hard-wired circuit boards of personal computer, but now residing in real-life objects with new wireless communicability. Chapters of this dissertation examine each different computer applicationโa navigation system in a smart car, smart home, open-world video games, and neuro-prostheticsโas each particular case of this object-oriented redefinition of human cultures
World of Warcraft Avatar History Dataset
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