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探讨WOW玩家角色名称及其行为的关联性

发布时间:2013-10-09 14:06:42 Tags:,,,

作者:anders drachen

调查背景

有时候,作为游戏分析专家,你会遇到一些没有直接实用性的工作,但它却是基本的、耐人寻味的。

这些研究的主题有时候是出自一群人聚在一起闲聊时引出话题。大约两年以前,在一次讨论会上,就像惯例,一群业界和学术圈的分析师开始吹嘘自己的MMO游戏角色取得了什么成就:

有人说:“HealBot是XX(某热门游戏的精英服务器的名称)服务器中最先满级的前十名玩家之一。”另一个人插话道:“哈,不就是成就嘛。NecroZeus有45000命值,是XX公会的头名玩家。”“你的角色还在穿纸尿裤时,ZonkarTheMighty就已经是第一位获得XXX(游戏中需要许多玩家合作才能得到的神器)的玩家了。”……

这场激烈的讨论意外地引出了关于玩家角色名称的话题——也许作为玩家的我们在命名自己的角色时是遵循一些模式或套路的。例如,在《魔兽世界》中,为什么圣骑士的名字总是与“Healbot”(治疗助手)之类的词相关,术士的名字经常与“Bloodmaster”(吸血大师)放在一起,血精灵——不考虑职业,通常使用带“Moonlight”(月光)的词。牛头人往往被扣上能体现其力量的名字,如“Mortar”或“EarthStomper”(撼地)。所以,我们决定调查一下这些假设。

Healbot(from wowinterface.com)

Healbot(from wowinterface.com)

收集数据

第二步大量收集《魔兽世界》(简称WOW)的玩家角色名称,我们一共收集了约1800万个。数量非常可观。但分析任务实在太重了,所以我们又把总数削减为约800万个,它们均来自美国和欧洲服务器中的前50大公会。本文所提到的名称已经预先处理了,即删除特殊符号,例如,“Gand’alf”就被简化为“Gandalf”。

调查的第一个发现是,《魔兽世界》的玩家在取名字方面真是太有才了。因为在不同的服务器中,玩家角色可以使用相同的名字,所以我们以为能把名字再次削减到380万个的希望落空了。尽管《魔兽世界》有命名限制,游戏世界的角色名字仍然比现实世界的要丰富多彩得多。为什么会这么多?我们只能猜测,这与玩家渴望塑造独一无二的角色有关——而名称正是《魔兽世界》中真正独一无二的特征。平均之下,58%的名称是独一无二的,但在RPG服务器中,83%的名称是独一无二的——然而,这是否说明了RPG玩家比PVP玩家更有创造力呢?不得而知。

显然,角色的职业和种族与名称选择之间是存在关系的。看看《魔兽世界》中最受不同种族和职业欢迎的名字,几乎不存在重叠。例如,魔法师的名字往往与术士的不同,牛头人的与血精灵的不同。也许意料中的是,名称频率遵循幂次定律(游戏邦注:这是在网络和游戏中不断出现的有趣模式)。

出于未知的原因,魔法师角色的名称要比其他职业的丰富得多。是玩魔法师的玩家更加有创意吗?更有自主精神?

Blood-Elf_histogram1(from gamasutra)

血精灵中的最热门名称(from gamasutra)

Mage_histogram1(from gamasutra)

魔法师中的最热门名称(from gamasutra)

WOWnames_humans(from gamasutra)

人族中最热门名称(from gamasutra)

事实上,等距映射表明,“漂亮的”种族(人类、血精灵、draenai等等)和“兽型”种族(半兽人、牛头人、不死族、巨魔、地精和矮人)形成对比鲜明的两个大类。也就是说,人们给漂亮的角色的名称与兽型角色的是非常不同的。奇怪的是,长得并不像野兽的地精和矮人居然也被归为兽型种族。这个结果导致我们猜测到人类心理学中某些令人不快的方面。

等距映射还表明,美国和欧洲服务器的角色名称形成不同的映射。RP服务器的角色的映射情况与PVP服务的很不同。有趣的是,RP服务器的名称在美国和欧洲有不少重叠。

eu_histogram1(from gamasutra)

欧洲服务器中最热门名称(from gamasutra)

us_histogram1(from gamasutra)

美国服务器中最热门名称(from gamasutra)

预测

在玩家行为的数据挖掘中,预测和估计给定职业/种族/服务器类型/等级等的条件概率是最常见的目标,对参与调查的分析人员来说多少有些令人吃惊。某些角色名称确实表明,有些名称是非常好的预测因素。职业和种族是最佳名称预测因素,特别是对于受流行媒体、书籍、电影、传说等启发而取的名称。

玩家如何想到这些名称?

我们对模式套路的说法并不满意,于是又人工寻找《魔兽世界》中最常用的1000个角色名称的灵感来源。我们的方法是手动语义编码。我们发现,现实世界中的好名字如Sara、Mia、Daniel等在游戏中最常出现(186次)。神话,特别是希腊神话中的名字出现了164次。流行文化(特别是日本漫画)衍生的名字出现了174次。奇幻文学,特别是托尔金的作品中的名字出现了39次。大量最流行的名称违反了《魔兽世界》的命名规定。许多名称基本上是抄袭了重要的NPC的名字。在这1000个最受欢迎的名称中,约300个是无法归类的。它们是由抽象的自然动词或名词组成的,但可以根据语义内容作粗略的归类。例如:

“消极的”:Nightmare(恶梦), Sin(罪恶), Fear(恐惧), Requiem(安魂)

“积极的”: Hope(希望), Love(爱), Pure(纯洁)

“中性的”: Who(谁), Moonlight(月光), Magic(魔法), Snow(雪)

带有消极语义的名称出现的频率是积极的6倍。这是否意味着玩家的心态比较阴暗?或者说“阴暗的”名字听起来更酷?

其他游戏的情况?

对《魔兽世界》的玩家角色名称的调查结果非常有趣,因为我们并没有指望在玩家角色名称数据中发现任何模式或套路。但它鼓励我们继续研究《魔兽世界》之外的游戏。通过研究其他类型的游戏,如FPS,也许我们能有幸发现关于玩家如何玩游戏、有什么样的操作风格和什么样的玩家标签的结论。

在像《孤岛危机》、《荣誉勋章》和《战地》系列等射击游戏中,玩家标签的表面价值与《魔兽世界》的角色名称是非常不同的。FPS玩家在给角色命名时,更经常地使用数字和特殊符号,把字母与数字相结组成没有直接关系的单词。比如,“MaliciousMaulr”、“x6naca6x”、“Ankur”、“HackJake0025”、“InSaNe_x_ChAoZz”和“Acid_Snake”等。

为了研究玩家标签与操作风格是否有关系,我们进行了不同的分析。第一个样本是通过各种聚类算法从《战地2:恶人连2》中取出的1万个玩家标签,看看玩家标签的结果群集是否与该游戏的玩家职业有关(即进攻、医疗)。

然而,结果表明,只有很小程度的非随机性,即玩家标签与最受玩家欢迎的职业的相关性很有限。我们又对从《战地》的行为遥测技术取得的7份操作风格资料进行相同的研究。这些信息是与游戏的核心机制有关的11个行为测量的集群分析的结果。这次,结果要好得多,表明在相当大量的玩家当中,《战地2:恶人连2》的玩家标签和行为文件之间确实存在关系(相关性达到61%)。

这样的研究有意义吗?

不能说我们的分析对改进《魔兽世界》的设计有指导性意义,或者对《战地》的玩家分析有直接的帮助。但它确实让我们更加深刻地了解玩家行为。确实,这种工作只能是一种探索性的、没有目标的游戏分析过程。然而,没有好奇心导向的基础研究,很多高科技成果如激光、微波或聚四氟乙烯都是不可能被发现的。有时候,好奇研究也会有回报。新游戏分析书籍中经常引用好奇心导向的游戏分析案例。所以,我们的这次研究也绝对是一种探索性的、有创意的分析。

也许我们的工作中最有趣的部分是,我们意识到研究结果有可能使我们能够根据玩家的角色名称预测某些游戏行为或甚至玩家个性中的某些方面。玩家/行为分析是包含角色/档案名称或玩家标签的新领域,是非常有意义的,但相关的数据仍然稀缺。(本文为游戏邦/gamerboom.com编译,拒绝任何不保留版权的转载,如需转载请联系:游戏邦

An Investigation of World of Warcraft Character Names

by anders drachen

Sometimes as a game analyst, you get to do work that does not have an immediately useful application, but which are just fun and basic, explorative research.

Such exercises sometimes begin when people get together socially after a long day and start speculating (glasses with variously colored liquids sometimes enter the picture as well). This was also the case when one day, almost two years ago, at a conference, a couple of analysts from the industry and academia started the customary ritual of bragging about the accomplishments of their characters in various MMOs – in an “artists interpretation” as follows:

“Yea, HealBot was among the first 10 to hit the level cap on [insert name of vastly popular and elite server in equally popular MMO]” one might say, with a colleague chiming in:“ha! As if that is an accomplishment. NecroZeus has 45,000 hit points [a lot] and is top-ranked in [insert suitably impressive guild name in major commercial MMO]”. “Your characters have barely matured from their diapers gentlemen – ZonkarTheMighty was first player ever to get the [insert name of impressive epic loot requiring dozens of player to coordinate their efforts]” – and so forth and so forth.

This lively debate unexpectedly led to a discussion about character names, and a speculation that there might actually be some sort of pattern in how we as players name our characters. For example, it was wondered why in e.g. World of Warcraft, Paladins were always called something along the lines of “Healbot”, Warlocks cool-sounding names like “Bloodmaster” and blood elves – irrespective of class – fancy names such as “Moonlight”. Taurens, it was argued, usually had names that deserved to have gravimetric force on their own, like “Mortar” or “EarthStomper”.  It was decided to investigate whether these hypotheses had any merit (and eventually a paper was written).

Enough exposition, get on with it …

The next step involved getting a hold of a ridiculous number of character data from World of Warcraft. About 18 million in total. This is a lot. And it made analysis cumbersome, so it was cut down to about 8 million, subsampled from the 50 biggest guilds on US and EU servers. Some pre-processing was done, e.g. removing special characters so that e.g. “Gand’alf” would be counted along with “Gandalf”.

The first result that became apparent was that players in World of Warcraft are incredibly talented at creating unique names. Characters with the same name can exist on different servers, so the mind-boggling 3.8 million unique names found in the dataset was not expected. This is more diverse than real-world names, despite the naming restrictions in World of Warcraft. Why this diversity occurs we can only speculate about, but it may relate to a desire to build a unique character – and the name is the only truly unique feature in World of Warcraft. On average, 58% of the names were unique – but on the Role-Playing servers 83% were unique – whether that speaks for the added creativity of RP’ers vs. those that favor PvP is unknown however.

Moving on, it is also evident that there is a relationship between the class and race of a character and the name selection. Looking at the most popular names for the different races and classes in World of Warcraft, there is virtually no overlap. For example, Mages have different names than Warlocks, and Tauren are named differently than Blood Elves. Perhaps unsurprisingly, name frequencies follow power laws (a very interesting set of models that keeps cropping up in internet- and games work).

For reasons unknown, Mages have a much higher variety of names than any other class. Any speculations as to why is welcome (are people who play Mages more creative? More independent-minded?).

Histogram of most popular Blood Elf race names

Histogram of the most popular Mage class names

Histogram of the most popular Human race names

In fact, isomap projection revealed that the “pretty” races (humans, blood elves, draenai, etc.) and the “bestial” races (orcs, tauren, undead, trolls – and gnomes and dwarves) formed two distinct groups. I.e. people name pretty characters very differently from the bestial ones (or however you want to define these races). Strangely, the otherwise non-bestial Gnomes and Dwarves map with the bestial races. This results leads into speculations about some uncomfortable aspects of human psychology that we will leave alone for now.

Isomap projection also revealed that character names on US and EU servers mapped differently. And that characters on RP realms mapped differently than those on PvP realms (with PvE and RP-PVP and other hybrids mapping with either parent group or in the space between). Interestingly, names for RP servers overlap across the US-EU divide.

Histogram of most popular names on the EU servers

Histogram of most popular names on the US servers

You mentioned prediction?

Prediction is one of the most common goals of data mining player behavior, and somewhat surprisingly to the analysts involved, estimations of the conditional probabilities of a given class/race/server type/level/etc. given a particular character name actually revealed that some names are very good predictors. Class and race emerged as the overall best predictors of names. This is especially the case when names are inspired by popular media, books, film, mythology etc. – more on this below.

Conditional probability of a given class / race / realm, given a particular character name

So, how do people come up with these names?

Not satisfied with patterns, the 1000 most common character names in World of Warcraft (roughly 138,000 characters total) were taken through a pain-staking process of manual examination and source of inspiration identification. The method used was manual semantic coding. This is a fancy way of saying the categories were made up as the names were investigated.  What was found was that real-world, vanilla names such as Sara, Mia, Daniel and so forth were the most common (186 names). Mythology, notably Greek, accounted for 164 names. Popular culture (notably Japanese manga and the characters invented by a certain Mr. Wheedon) accounted for 174. Fantasy literature, with Tolkien ruling supreme, accounted for 39 names. A lot of the most popular names were in breach of the terms of use of World of Warcraft. Many names were basically copies of important NPCs. About 300 of the 1000 most popular names could not be classified. These were names consisting of verbs or nouns of unspecified nature, however, they can be categorized based loosely on semantic content.  For example:

”Negative”: Nightmare, Sin, Fear, Requiem

”Positive”: Hope, Love, Pure

”Neutral”: Who, Moonlight, Magic, Snow

The names with negative semantic connotations were six times more common than those with positive connotations. Does this mean gamers are depressed? Or do “dark” names just sound cooler?

What about other games?

The World of Warcraft results were intriguing because we honestly did not expect to find any patterns in the character name data. But it encouraged us to look beyond World of Warcraft. Looking to another genre, the FPS, it was decided to try our luck with investigating whether it is possible to say anything about how a person plays a game, their playstyle so to speak, and their gamer tag.

Gamer tags in shooters like the Crysis-, Medal of Honor- and Battlefield-series are at face value very different than World of Warcraft character names. The use of numbers and special characters is much more frequent, as is combinations of letters and numbers that do not have any direct resemblance with words. A quick look over on the P-stats network throws up examples like “MaliciousMaulr”, “x6naca6x”, “Ankur”,  “HackJake0025”, “InSaNe_x_ChAoZz”, and “Acid_Snake”.

In order to investigate if there are relationships between gamer tag and playstyle, different analyses were run. The first ran a sample of 10,000 gamer tags from Battlefield 2: Bad Company 2 through a variety of clustering algorithms and distance measures useful for string clustering, seeing if the resulting clusters of gamer tags correlated with which Battlefield 2: Bad Company 2 class (e.g. Assault, Medic) the player in question favored. The result revealed however only a small degre of non-randomness, i.e. that gamer tags only to a limited degree relates to the most favoured class of a player. Moving on, we tried the same thing with seven playstyle profiles built from behavioral telemetry from Battlefield. The profiles were the result of earlier cluster analysis of 11 behavioral measures related to core mechanics of the game. This time the result was a lot better, indicating that there is a relationship between gamer tag and behavioral profile in Battlefield 2: Bad Company 2 for a pretty significant chunk of the players (cluster purity measures reached 61%).

Okay, but is this useful?

It cannot be claimed that the analyses provided direct insights in how to improve the design of World of Warcraft nor stunning insights for the players of Battlefield. It does provide insight into the players though. Irrespective, this kind of work falls squarely into the explorative and non-goal driven category of game analytics processes discussed here. However, without curiosity-driven and basic research, we would not have the laser, the microwave or teflon. Sometimes this kind of approach pays off. The new game analytics book includes examples of curiosity-driven game analysis leading to important conclusions. So this is definitely not an argument against being explorative and creative in analytics.

Perhaps the most intriguing part of the work we did is the hints that it may be possible to predict some aspects of play behavior or perhaps even personality of people based on their character names. Player/behavioral profiling is another area where including character/profile names or gamer tags could be of interest, notably in sparse-data situations.(source:gamasutra)


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