Proceedings:BL1/zh-hant

Wikimania 2007 Taipei :: a Globe in Accord

這是2007年國際維基媒體年會預定議程的一部分 (預定議程目錄)

特輯:新手的貢獻─新註冊會員的行為研究

作者 Brianna Laugher (墨爾本大學)
分類 維基媒體社群
版權 GNU自由文檔許可證 (詳情)
有關 作者

Presenters/Brianna Laugher/Biography

摘要
每日,在英文維基百科上都有一萬多個帳號登記,是什麼何以驅使讀者登記帳號呢?其中又有多少帳戶是為了要搞破壞而隨後又被封鎖的呢?那些為了真正想編輯的註冊用戶又有多少會堅持下去?是什麼讓他們如此貢獻?有那些條目是新用戶特別感興趣於編輯的呢?其他用戶又如何與之互動呢?

在缺乏詳盡用戶整體調查的情形下,這項報告將會以初步的統計資料及深入的分析來研究新用戶的貢獻,並提供些「新手管理」的改進方案。

在2007三月,新註冊的用戶數大約在7076至10958間,平均為9390個帳號。先不管這超高人氣,我們對於這些在英文維百(或其他語言的版本)所註冊的新用戶毫無所悉。我們僅能靠經驗來臆測。這缺乏資料的情形讓我們無法了解這些用戶的背景、他們是如何進入維基世界的。我們無法得知這些人是怎麼登記的、他們的目的為何。我們無法理解這些人為何登記了卻又從不在維百上編輯。我們不知道那些規則、方法是新用戶無法了解或著最能接受的。我們不知道他們是否發覺到有用戶社群的存在,如果答案為是,他們是如何感覺參與其中的呢?若無法回答這些問題,「新手管理」將只是一個無計畫的活動。

藉著維基媒體wiki系統所提供的強大工具─能追蹤個人活動記錄的「用戶貢獻」頁及"Block log"、"Upload log"等日誌,我們將能進行「online ethnographer」的調查。我們將會分析在當日(例如2007年的一月31日)內新註冊用戶所有的行動。我們並會觀察他們與社群互動的情形,像是「對話頁」的利用。緊接著的問卷調查將提供補充的資料以便探究典型新用戶的數量、其動機和經歷。Results will be summarised with reference to the existing literature on virtual ethnography. Comparisons to typical experiences in social networking websites and FLOSS (Free/Libre/Open-Source Software) projects will be highlighted.

廣受全球使用的英文維基百科身為維基媒體最重要且知名度最高的計畫,這些可貴的資料將提供其他計畫參考學習的來源。當其他wiki計畫成熟茁壯至英文維百的規模後,他們也將會有好的榜樣。Ultimately a data-based view can inform a holistic approach to new-user socialisation in order to retain and support the highest possible rate of productive (as defined by the existing community) users.

Every day ten thousand accounts are registered on the English Wikipedia. What motivates readers to register? What percentage of accounts are used for vandalism and subsequently banned? Of those accounts used for editing, how many go on to become productive community members, and what influences them to do so? Which pages do new users tend to edit? How do other users interact with them?

In the absence of a General User Survey, this paper will present some baseline statistics and an exploratory analysis of the contributions of recently registered users. Recommendations for improving "newbie handling" will be made.

In March 2007, the number of accounts registered on the English Wikipedia each day ranged from 7076 to 10958, averaging 9390. Despite its huge popularity, little to nothing is formally known about the users who register on this (or any other) Wikimedia wiki - we can only surmise based on our own experiences. This lack of data precludes us from understanding how new users approach and interact within the wiki. We do not know who is registering or what their motivation is. We do not know why many people register accounts but never use them to edit. We do not know which policies or processes new users struggle to understand, or even which they tend to encounter first. We do not know if new users perceive that a user community exists, and if they do, we do not know how they act to feel included. Without answers to these questions, "newbie handling" (socialisation of new users into, ideally, productive community members) can be ahaphazard activity at best.

A MediaWiki wiki offers particularly powerful tools to the "online ethnographer": the Special:Contributions page, by which one's wiki activities can be tracked, and public logs such as the "Block log" and the "Upload log". This presentation will analyse the contributions and logged activities of all users who registered on a single day (for example, January 31 2007). It will also analyse how the users interact with the community, by way of the users' talk pages. A follow-up questionnaire will provide supplementary data to analyse the demographics, motivation and experiences of typical new users. Results will be summarised with reference to the existing literature on virtual ethnography. Comparisons to typical experiences in social networking websites and FLOSS (Free/Libre/Open-Source Software) projects will be highlighted.

As the English Wikipedia is the most popular Wikimedia project and now a website known and used worldwide, such data will prove a valuable resource in an understudied area. As other wikis mature to the size and popularity of English Wikipedia, comparisons of growth patterns will be possible. Ultimately a data-based view can inform a holistic approach to new-user socialisation in order to retain and support the highest possible rate of productive (as defined by the existing community) users.

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