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博碩士論文 etd-0805118-085236 詳細資訊
Title page for etd-0805118-085236
論文名稱
Title
使用Steam平台之社群網路尋找遊戲團體
Finding Gaming Groups via the Social Network on Steam Platform
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
32
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2018-09-03
繳交日期
Date of Submission
2018-09-09
關鍵字
Keywords
Steam平台、數位遊戲、社群、相似度、團體組成
Steam Platform, Digital Game, Social Community, Similarity, Group Formation
統計
Statistics
本論文已被瀏覽 6143 次,被下載 92
The thesis/dissertation has been browsed 6143 times, has been downloaded 92 times.
中文摘要
現今有許多數位遊戲發行平台誕生,而其中使用人數最多的便是由Valve公司所推出的Steam平台。它不但提供遊戲販售的功能,還提供了數位版權管理功能,讓使用者可以使用Steam來啟動遊戲並遊玩,也因此使用者的遊玩行為能夠被觀測到。同時,Steam也提供了社群功能,讓使用者可以在平台上建立社群及互動。因此Steam不但是一個遊戲販售平台,也是一個遊戲管理平台,同時還是一個社交平台。於是我們嘗試在這樣的平台上,利用其多功能性的特色,去幫使用者解決尋找遊戲夥伴的問題。我們利用平台上的公開資料,也就是使用者的遊戲清單、遊戲時數、即時動態、好友列表去計算出使用者間是否適合一起玩遊戲,並為其尋找出適合的遊戲夥伴,組成遊戲團體。
Abstract
There are many digital game distribution platforms today, and Steam, which developed by Valve Corporation, has the most users. Steam not only provides game selling features, but also provides digital rights management features, allowing users to launch games and play it on Steam. That makes the user's playing behavior can be observed. At the same time, Steam also provides community features that enable users to build social communities and interacting with each other on the platform. Therefore, Steam is not only a game selling platform, but also a game management platform and a social platform. Due to the versatility of Steam, we try to solve the problem of finding game partners. We use the public information on Steam, that is, the user's game list, play time, current activity status, and friend list to calculate whether the user is suitable for playing games together by similarity. And then find suitable game partners for them to form a gaming group.
目次 Table of Contents
第一章、緒論 1
1.1 研究背景 1
1.2 研究動機與目的 1
第二章、文獻探討 3
第三章、問題描述 9
第四章、資料集 10
4.1 資料集分析 10
第五章、方法 12
5.1 遊戲相似度 12
5.2 時段相似度 13
5.3 社交距離 15
5.4 適合度 15
5.5 演算法 15
第六章、實驗 17
6.1 實驗內容 17
6.2 計算 19
6.3 結果比較與分析 20
第七章、結論與未來展望 22
7.1 研究限制 22
7.2 未來展望 22
參考資料 23
參考文獻 References
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