「互動行為」成為玩家在大型多人線上角色扮演遊戲當中，產生遊戲愉悅的一大因素（Kerr, 2006；Cole & Griffiths, 2007）；互動性愈強的線上遊戲通常愈能吸引住玩家。因此，「互動行為」對線上遊戲而言極為重要。
然而，如Freeman（2004）所說，主流的社會研究幾乎都將焦點集中在個體的行為上，忽略了個人的行為與人際關係之間彼此影響的社會層面，而線上遊戲相關研究也面臨此問題。因此，本研究之目的即在探討線上遊戲玩家之社會關係網絡，以及其自我中心網絡對玩家行為互動模式之影響。
本研究總計調查337名線上玩家，訪問玩家的夥伴名單、自我中心網絡與行為互動模式。經研究發現，扮演男性角色的玩家，在技術性之互動行為較為熟練；參與公會之玩家其自我中心網絡較為廣闊與深厚。本研究證實玩家的自我中心網絡會對其行為互動模式產生正向之影響。友誼關係通常連接著強連繫，初識關係則連接著弱連繫；其兩者皆能對玩家之行為互動模式產生影響，但相對影響性則是友誼關係較高於初識關係。

The interaction in massively multiplayer online role-playing games（MMORPGs）form a considerable component in enjoyment of playing（Kerr, 2006；Cole & Griffiths, 2007）. So player is attracted by the more interactive online gaming. Therefore interaction is extremely important for MMORPGs.
However, according to Freeman (2004), much of the research focused on individual behavior, but ignored the social dimensions of the influence between relationships and individual behavior. The research of online gaming has neglected that too. Therefore, the purpose of this study is to explore how is the social network of MMORPGs players in the game？And what effect will social network have on players’ interaction patterns？
In this paper, the survey has been completed online by 337 players, who reported on their buddy list, ego-centered network, and interaction patterns. This study explored that male role is more skilled in technical behavior；the social capital of players involved in online gaming communities is more prosperous. It is found that the ego-centered network of players positively affects players’ interaction patterns. Friendships are connected with strong ties, but acquaintances are connected with weak ties. Both of them could affect players’ interaction patterns, but the influence of friendship is relatively higher than that of acquaintance on players’ interaction patterns.

目 錄
論文審定書
誌謝 i
中文摘要 ii
英文摘要 iii
第 一 章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 3
第三節 研究問題 4
第 二 章 文獻探討 5
第一節 線上遊戲相關研究 5
第二節 線上遊戲玩家互動行為 15
第三節 線上遊戲虛擬社群 24
第四節 社會網絡理論 28
第 三 章 研究設計 33
第一節 研究架構 34
第二節 研究工具 34
第三節 研究對象 34
第四節 問卷設計 35
第五節 問卷執行與收回 39
第 四 章 資料分析 41
第一節 樣本分析 41
第二節 量表信效度分析 46
第三節 玩家人口變項與角色特徵分析 50
第四節 主要研究變項與玩家角色特徵分析 51
第五節 研究變項間之相關分析 55
第六節 迴歸分析 57
第 五 章 研究結論與建議 63
第一節 研究結論 65
第二節 研究限制與建議 69
參考文獻 71
附錄一 問卷前測 81
附錄二 正式施測問卷 86

圖　次
圖2-1 線上遊戲公會組織架構 27

表 次
表2–1 線上遊戲玩家動機研究 8
表2–2 線上遊戲玩家忠誠度研究 8
表2–3 線上遊戲玩家遊戲行為研究 9
表2–4 線上遊戲玩家網路成癮研究 10
表2–5 線上遊戲玩家特性研究 10
表2–6 線上遊戲玩家性別研究 11
表2–7 線上遊戲玩家互動研究 11
表2–8 線上遊戲玩家人口屬性 13
表2–9 玩家互動行為研究 17
表2–10 各項溝通行為與遊戲互動行為對照統整表 24
表3–1 虛擬社會網絡連繫強度問卷 36
表3–2 行為互動模式量表 37
表4–1 樣本描述性統計 42
表4–2 樣本描述性統計 43
表4–3 互動人數描述性統計 44
表4–4 玩家角色性別交友描述性統計 45
表4–5 玩家角色定位交友描述性統計 45
表4–6 玩家與互動對象之關係描述性統計 46
表4–7 行為互動模式量表因素分析 47
表4–8 自我中心網絡問卷信度檢測 49
表4–9 性別與角色性別之卡方檢定 50
表4–10 性別與角色定位之卡方檢定 50
表4–11 性別與公會參與之卡方檢定 50
表4–12 角色性別對公會參與之卡方檢定 51
表4–13 公會參與對角色定位之卡方檢定 51
表4–14 角色特徵對行為互動模式之T檢定 52
表4–15 角色特徵對行為互動模式之變異數分析 53
表4–16 角色特徵對自我中心網絡之T檢定 54
表4–17 角色特徵對自我中心網絡之變異數分析 55
表4–18 主要研究變項間之相關矩陣 56
表4–19 自我中心網絡總分預測行為互動模式總分 58
表4–20 自我中心網絡總分預測規範性溝通行為 58
表4–21 自我中心網絡總分預測規範性溝通行為（再次分析） 58
表4–22 自我中心網絡總分預測策略性戲劇行為 58
表4–23 自我中心網絡總分預測策略性工具行為 59
表4–24 初識關係與友誼關係預測行為互動模式總分 59
表4–25 初識關係與友誼關係預測行為互動模式總分（再次分析） 59
表4–26 初識關係預測行為互動模式總分 60
表4–27 初識關係與友誼關係預測規範性溝通行為 60
表4–28 初識關係與友誼關係測規範性溝通行為（再次分析） 60
表4–29 初識關係預測規範性溝通行為 61
表4–30 初識關係預測規範性溝通行為（再次分析） 61
表4–31 初識關係與友誼關係預測策略性戲劇行為 61
表4–32 初識關係預測策略性戲劇行為 61
表4–33 友誼關係預測策略性戲劇行為 62
表4–34 初識關係與友誼關係預測策略性工具行為 62
表4–35 初識關係預測策略性工具行為 62
表4–36 朋友關係預測策略性工具行為 63

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