Andreas Weigend 2. August 2007 | Düsseldorf

Presentation on theme: "Andreas Weigend 2. August 2007 | Düsseldorf"— Presentation transcript:

1 Veränderungen in einer vernetzen Welt – die METRO Group im neuen Mitmach-Web
Andreas Weigend 2. August 2007 | Düsseldorf people & data | weigend.com

2 What is Web 2.0? Tim O’Reilly (2005): Web 2.0 is
a set of economic, social, and technology trends that collectively form the basis for the next generation of the Internet—a more mature, distinctive medium characterized by user participation, openness, and network effects.

3

4 Person of the Year (Time Magazine, 2006.12)
时代周刊2006年度人物 是的，就是你！你掌控信息时代！欢迎来到你的世界·！

5 Agency of the Year : The Consumer (Advertising Age 2007.01)
年代理商：消费者广告时代

6 The five levels Community Interaction Participation Experimentation Data Web 2.0 But not about definitions, more about understanding patterns and applying them to what we do Web 1.0

7 Web1.0 vs Web2.0 Web1.0 与 Web2.0 Web 1.0 : E-business Web 1.0 ：电子商务
about pages, commerce 关于网页和商业 Data gathering 数据搜集 Experimentation 试验 about impressions 关于印象 Web 2.0: Me-Business Web 2.0：我的商务 about people, individuals 关于人和个人 Participation, Contribution 参与，贡献 Interaction 互动 Group, Community, Collaboration 团体，社区，协作 Crowdsourcing more than social networks 不同于社会网络的扎堆 Future of work 未来的工作 about the impressed 关于留下印象的

8 Web1.0 vs Web2.0 Web1.0 与 Web2.0 Web1.0 Web2.0 Read-only 只读网页
Read + write 可读写网页 Consumer 消费者 “Prosumer” = Producer + Consumer 生产者 + 消费者 User 使用者 “Youser” 你 High barrier of exit (stickiness) 高的退出壁垒（粘性） Low barrier of adoption 较低的进入壁垒 Pretest and validate 预先测试和验证 Launch and learn; Push and pray 发起和学习；推进和请求 Taxonomy (controlled) 基于超链接的探索（体现出作者的控制） “Tagsonomy” (not controlled) 标签法（不受控制的）

9 From Targeting to Discovery 从定位到发现
Web 1.0 Web 2.0 Discovery based on hyperlinks (expressing control of author) 基于超链接的探索（体现出作者的控制） Discovery based on social relations (trust, reputation) 基于社会关系的发现（信任，信誉）以及其他人的元数据。 Push: Supply driven. 推式广告：供给驱动 Pull: Demand driven 拉式发现：需求驱动 Target 目标定位 Search 搜索 Discover 发现 LIUJUN: Please make table with round corners into style sheet, like the new top

10 Attributes of Web2.0 User focus (E-Business  Me-business)
User is at the center of Web2.0 Transparency Google Maps: Create API rather than tighten security Technology Lightweight System engineered for feedback System improves as people use it Network effects Demand-side economies of scale (not only supply-side economies of scale) Incentives Pay people (e.g., Yahoo directory index) Get volunteers (e.g., wikipedia) Create self-interest (e.g., BitTorrent; file sharing sites)

11 Discovery: Rich content onto mobile via Bluetooth

12 Web 1.0  Web 2.0 Web 1.0 Web 2.0 Background (2007)
1 bn PCs, 2 bn mobile phones 150M registered eBay users, more transactions per day than NYSE 80M blogs total, 20 new entries per second, 2 new blogs created every second US online advertising USD 15…20bn (12.5bn in 2005) Web 1.0 Web 2.0 Power Companies need to be protected from users Users need to be protected from companies Core Algorithms Data Hardware SUN etc Commodity PCs Software Oracle etc LAMP (Linux, Apache, MySQL, PHP) System often deteriorates over time System engineered to improve over time by leveraging user data Technorarti nr Paid Search nur

13 Technology innovation
Military Enterprise Consumer Centralized Top-down Consumer Enterprise De-centralized Bottom up

14 User generated content (UGC) 用户自创内容
Paying a few experts to create content  Users generated content 雇几个专家来创造内容用户自己创造的内容 Implicit data and explicit data 隐含的数据+明确的数据 Incentives? 激励运作? Metadata 元数据 Example: Music 例子：音乐

15 Social search 社会搜索 Algorithmic search  Social search 规则搜索社会搜索
Use information of files, etc. on your computer to determine relevance 使用你的电脑文件里的信息来决定相关性 Example: Illumio 例如：Illumio Customers helping customers: People answer questions 消费者互助: 人们回答问题 Exmple: Yahoo Answers 例如：Yahoo Answers

16

17 Social search – Korea 韩国的社会搜索
KoreanClick Naver 77% of searches 占77%的搜索 110M queries per day by 16 M unique users per day out of 48M citizens 4800万人口中，每天有11000万条询问 来自于1600万个用户 Knowledge iN (since 2002) Knowledge iN（始于2002年） 44k questions posted per day 每天有44000条问题 110k answers received per day 每天会收到110，000条回复 Cumulative 70M 累计达到7000万条 Other search engines Daum.net 11% Daum.net 占11% Yahoo 4.4% Yahoo占4.4% Google 1.7% Google占1.7%

18 Knowledge Search, Yahoo 2003 in Korea 韩国版的Yahoo知识搜索工具

19 Popular questions in Korea 什么问题在韩国最流行？
Why do people close their eyes while they are kissing? 为什么人们接吻的时候要闭上眼睛？ The most common name in the world? 世界上最通用的名字是什么？ What’s the truth of Bruce Lee’s death? 李小龙的真正死因是什么？ Why do people get drunk more when drinking alcohol with a straw? 为什么当人们使用吸管喝酒的时候更容 易喝醉？ Are there any animals that commit suicide? 什么动物会自杀？ Is that true that most of The Great Commanders are short? 大多数的大人物都很矮，这种说法对吗？ Why is the Ocean salty? 为什么海水是咸的？ Why do people lift up their hands to show their joy of victory? 为什么人们要举起手来表示他们胜利的 喜悦？ The Secret of Popularity of Harry Potter Series!! 哈里波特系列如此畅销的秘密。 Badly want to lose my weight.... Help. 非常非常想减肥….请帮忙！ Knowledge search has become the

20 Amazing user adoption… 网络搜索的惊人增长
每周的网页浏览数 知识搜索

21 …with a Web search halo 网络搜索的惊人增长
每周的网页浏览数 网络搜索 知识搜索

22 Yahoo Taiwan: Design Yahoo台湾：设计

23 Yahoo Taiwan: Launch 2004.12 Yahoo台湾（2004年12月诞生）
Total Search Market Share (PVs) Yahoo! 68% Google 29% MSN 1.5% Total Search Market Reach Total Search Market Reach Total Search Market Share (PVs) 总的搜索市场范围 总的搜索市场份额 Yahoo! 89% Yahoo! 68% Y! Knowledge 67% Google 51% MSN 24% Source: InsightXplore ARO

24 Yahoo Answers US: Design Yahoo Answers美国：设计

25 Yahoo Answers US: Launch 2005.12 Yahoo Answers美国（2005年12月诞生）
Answer.yahoo.com Answer.google.com Qna.com.com

26 Typical interaction 典型的互动
Example: I need a 7th grade science experiment using food and how quickly it molds 例如：我需要七年级的用食物 来观察多久发霉的科学实验 48 mins ago

27 US web search 美国的网络搜索 US web search market share: Y! flat, Google taking share from MSN and AOL 美国的网络搜索市场份额：Yahoo和Google超过了MSN和AOL Jason Check flags – didn’t show up when going through the preso Check Taiwan numbers Source: Comscore qSearch reports Quarterly data reflects end of period data

28 Landscape of Web Search 网络搜索行业的特点
Levers to gain market share 两个赢得市场份额的要素 Superior quality Distribution 质量和分销渠道 Mechanisms to lock-in share 锁定市场份额的办法 Differentiated content 差异化的内容 Superior monetization 较好的货币化 Country leader has advantage 本土领先优势 US (Google), KR (Naver), CN (Baidu) Google在美国，Naver在韩国，Baidu在 中国 New players face significant barrier to entry 进入壁垒高 Brand and user habits dominate 品牌和用户习惯起主导作用： - Europe is to win the middle and small Hosted Search - Maxthon (browser)- Maxthon (browser)

29 Social search has the potential to change the game Social search 很有可能改变游戏规则
Consumer need 消费者需求 Platform enabling communities of people to share 创造世界上最大的平台，使交易各方 能够共享来自于经验的和后来学习的 知识 Experiences Long tail knowledge Game changing potential 游戏规则改变前景 Critical mass of content and community of knowledge enthusiasts 创造一个必不可少的信息群以及一个 由热心人建立的知识社区 Change the search experience 改变搜索经历

30 Where will this lead? 这会导致什么现象出现？
DJ’s ask for Answers as part of their show programming 7 音乐主持人使用Answers作为节目的一部分 明星，思想领袖阐述他们的观点或者知识的时候更多的引用网络链接 Level 6 – Home & Garden Celebs, thought leaders, give out urls for more on their views & knowledge Pop culture mentions Answers frequently and in the context of broader issues – not as a promotion 时兴文化经常会在更多的情形下提到Answers—这并不是在推广

31 Where will this lead? 这会导致什么现象出现？
当地列表包含Answers的层次证据 7 Local listings contain answers level credentials Professionals quote Answers levels as credentials Level 6 – Home & Garden 专家引用Answers作为证据 Level 6 – Home & Garden Answers成为对关键事件和政治事件进行社会争论和事实交换的中心 Answers becomes the epicenter of social debate and fact exchange around key issues & political events

32 Why is this game changing? 为什么游戏规则会改变？
Person with a Question? 有疑问的人 Share Knowledge 知识共享 Ask Answers 询问答案 Ask ask family/friends Google/Yahoo Blog Facebook Wikipedia . . . Share Person with Knowledge 有答案的人

33 Learnings 经验之二 The expertise is in the tail 专家位于尾部（占少数）
It’s about the people 以人为本 怀孕和做父母的最佳答案

34 Use in politics: Hilary Clinton asking about healthcare
根据你的个人家庭生活经验，你认为应该怎样提高美国的健康护理水平？

35 Social Networks (“Contacts”) 社交网络（“联络”）
Build your knowledge network by connecting with the people you trust and the topics you care about 通过与你信任的人和你关心的问题联 系建立你的知识网络 Benefits 好处 More personal experience 更私人化的经历 More productive experience 更有成果的经历 Faster, easier access… 更快 … to more useful, helpful, relevant information 更简单地找到更有用、更相关的信息

36 The five levels Web 2.0 Web 1.0 Community Interaction Participation
Experimentation Data Web 2.0 Web 1.0

37 Increase of Communication: Five levels 增进沟通的5个层次
Architectures of Collaboration, Community 协作社区体系 Architectures of Interaction 交互体系 Architectures of Participation 参与贡献体系 Remember, share, discover 记住，共享，发现 Empower and incentivize people to contribute 给予人们贡献的权力并激励他们来贡献 Architectures of Experimentation 实验体系 Act: A/B test, active learning, surveys … 做法：A/B测试，主动学习，问卷设计… Data Strategy 数据收集分析 Collection, mining: Describe, predict 数据挖掘：描述，预测 Web 2.0 LIUJUN: PLEASE MAKE THIS PYRAMID, WHERE COMMUNITY IS ON TOP (i.e., reverse order_ Web 1.0

38 1. Data collection and analysis (Amazon.com) 1.数据收集和分析(Amazon.com)
Data collected in 年搜集的数 据 100 MB 10 GB 1 TB 100 TB Level 层次 Customer 消费者 Orders 订单 Session aggregates 访问总计 Clicks 点击 Amount of data 数据量 ASW: Compare to Facebook ASW: Check numbers Same as google logs: 100G / day Largest lab for people data Vision summary E.g., to compute convergences “Information age” Interaction effects Visit Level / could talk about Visit Level (daily aggregates) WHY?? ADD BENEFITS MORE: Site instrumentation 网址工具 JavaScript (Mouse movement, scrolling鼠标移动、滚动)

39 Sources of data Order data 订单 Attention data 关注数据
E.g., Amazon.com 例如：亚马逊网站 A few GB per year 每年几百亿 Click data 点击数据 E.g., Facebook web logs 例如：Facebook网络链接 A few TB per day 每天几万亿 Intention data 意图数据 E.g., Google search logs 例如：google的搜索网页 Attention data 关注数据 E.g., Del.icio.us tags 例如Del.icio.us Interaction data 信息数据 Social network data, headers 从社会网络，从电子邮件标题 Location data 地点数据 GPS, mobile phones 从全球定位系统，从移动电话

40 Web 1.0 vs Web 2.0 Web 1.0与Web 2.0 Web 1.0 Web 2.0 DoubleClick -->
Web 2.0 DoubleClick --> Google AdSense Ofoto Flickr Britannica Online 英国在线 Wikipedia personal websites 个人网站 Blogs 博客 domain name speculation 投机域名 search engine optimization 搜索引擎优化 pay by impression 按显示计费 pay for click 按点击计费 screen scraping 刮屏 web services 网络服务 Publishing 发表 Participation 参与 directories (taxonomy) 目录（分类法） tagging (tagsonomy) 标书签（书签分类法） Stickiness 黏性 Syndication 企业联合组织

41

42

43 3. Participation 3.参与 1. Data Analysis 数据分析
Data mining: Description, prediction 数据挖掘：描述，预测 2. Architectures of Experimentation 实验体系 A/B test, active learning, survey design… A/B测试，主动学习，问卷设计 3. Architectures of Participation 参与体系 Remember, share, discover 记住，共享，发现 Empower and incentivize people to contribute 给予人们贡献的权力并激励他们来贡献 Self-expression 自我表达

44 Platform: Yellow Pages 平台：黄页
LIUJUN: more bright color for the rectangle

45 Click to Call Business Click to Call! 点击 直接通话

46 Make customer feedback trivially easy 获取消费者反馈易如反掌
Capture context automatically 自动捕获内容 I went to the bathroom and came back, and the page was still loading!! 我去了浴室，又回来，网页却还在下载！！

47

48

49

50 Money Economy  Intention Economy  Attention Economy 货币经济意图经济注意力经济
Click 点击 Depends on choice set Only able to click on links given on site. 只能点击网站链接

51 From intention to attention 从意图到注意力
Click 点击 Search 搜索 Express intention. Doesn’t depend on result. 表达意图。独立于结果 Depends on choice set Only able to click on links given by site. 只能点击网站链接

52 From intention to attention 从意图到注意力
Click 点击 Search 搜索 Tag 书签 Amount of specificity increases 针对性愈加明显 Label item. To remember, share，discover. 留下标签。记忆，共享，发现 Express intention. Doesn’t depend on result. 表达意图。独立于结果 Depends on choice set Only able to click on links given by site. 只能点击网站链接

53 Example: del.icio.us 例子：del.icio.us
Tags are distilled attention, a pure form of attention. 书签是过滤的了注意力，是纯粹的注意力 You are what you tag. 书签展示真我 You are what you are tagged as / who you are tagged by. 书签决定你的存在 Follow a tag and discover a topic 跟随书签发现话题 Discover other users who tagged the page 找到给同一页面贴上书签的其他网友 Follow a user and discover what he is interested in 探索该网友的兴趣爱好

54 Example: flickr 例子：flickr
Quentin Lee, Filmmaker (Drift, Ethan Mao) 你想评论一下吗？

55 If you remember one thing…
Not only business… Also:Society

56 The Tectonic Shift in Trust 信息的结构性转变
The Age of Deference 服从时代 The Age of Reference 关系时代 Most trusted source 信任度最高 The man on the street Friends and family Alternative opinions Celebrities Established authorities Elders Leaders 领导 Leaders Elders Experts Celebrities Alternative opinions Friends and family The man on the street 长者 专家 名人 Tectonic Shift 结构转变 jie 2 gou 4 zhuan 3 bian 4 Reference 参考 can 1 kao 3 备选方案 亲友 Least trusted Source 信任度最低 陌生人

57 What is happening now? 新世界
Empower millions of users to contribute 上百万网民共同参与 del.icio.us: tag web pages 网页书签 flickr.com: tag photos 照片书签 43things.com: tag life goals 目标书签 LIUJUN: Arrows horizontal ASK: Community vs experts: pros and cons One-to-many 一对多 Many-to-many 多对多

58 来源Source: Valdis Krebs
Network of Books based on Customers who Bought Also Bought 书籍网络：买这本书的人也会买那本 来源Source: Valdis Krebs

59 What blogs link to weigend.com? 有哪些博客有weigend.com的链接？

60 Chris Anderson’s blog: LongTail
Chris Anderson’s blog: LongTail.com (Aug entry) Chris Anderson的博客：LongTail.com(2006年8月16日)

61 LILY: Need chinese translation
Perha[s need to do redo slide? 来源Source: Chris AndersonWIRED, Oct 2004

62 长尾效应

63 Recommendations create demand in the “long tail” “长尾效应”中的推荐刺激需求
39% of Turns from titles ,000 50% of Turns from titles 1,150-30,000

64 4. Interaction 4.交互 1. Data Analysis 数据分析
Data mining: Description, prediction 数据挖掘：描述，预测 2. Architectures of Experimentation 实验体系 A/B test, active learning, survey design… A/B测试，主动学习，问卷设计 3. Architectures of Participation 参与体系 Remember, share, discover 记住，共享，发现 Empower and incentivize people to contribute 给予人们贡献的权力并激励他们来贡献 Self-expression 自我表达 4. Architectures of Interaction 交互体系

65 Platform: eBay feedback (ratings, reputation system) 平台：eBay反馈(评级，信誉系统)

66 Who is checking me out? 谁浏览了我的网站？
最近浏览了我的 联系页的成员

67 Xing/LinkedIn, openBC Monetization 货币化 Innovation 革新 Advertising 广告
Subscriptions 订阅 Especially Recruiting / Headhunting 招聘/猎头 Innovation 革新 Auto-create resumes, and make it easy for people to edit their own resumes 自动生成简历以便随时编辑

68 Dating (Match.com, Fridae.com, …) 网上交友(Match.com, Fridae.com, …)
Monetization 货币化 Subscription 订阅 But since inventory is key, need to also have a free version (network effect) 因为库存是关键，也需要有免费版本(网络效应) Advertising 广告 Innovation 创新 Ranking bi-directional (as one choice) 双向排序(作为选择) Ranking based on implicit behavior 基于隐秘行为排序 Data mining to understand physical advertising 数据挖掘以理解实物广告 Modeling modalities vs asking explicitly 规律建模与直接询问 Reputation, domain specific 名誉，特定领域 General problem 普通问题 Demand very uneven 需求很不均匀 Very attractive or influential people get more traffic than they want, and have very little to gain from the list, and then unsubscribe 非常引人注目或者有影响的人得到过多访 问，而并未从列表中获利多少，所以可能 取消注册 Need to create a currency (such as ‘virtual red roses) 需要创建流通货币(如虚拟红玫瑰)

69 Online Personals and Dating 网上社交和约会
2004 market size: $ 1 billion 2004年市场规模：10亿美元 Most profitable online content! 最有利可图的网上内容！ Current doubling time: 1 year 目前翻番的时间跨度：1年 match.com 1M subscribers ($20/month) 100万注册用户（每月会费20美元） Churn “problem” 会员流动“问题” Average customer lifetime 3-5 months 注册用户的平均持续期为3-5个月 1/3 of subscribers that quit re-subscribe within 12 months 注销的用户中有1/3在12个月内重新注册 friendster.com 3M subscribers (10/2003) 300万注册用户（截至2003年10月） And more… 更多…… Mobile phone dating 手机交友 New Numbers 1.2bn dating market (onnline + offline) m/c problem

70 Sept 2003 U.S. snapshot: 27M males age 18-34 on Web 美国2003年9月概况：2700万18-34岁的男性网民
Males in U.S. age 18-34　 美国18-34岁的男性 Total users：27M 因特网用户数: 2700万人 (= 100%) Adult Sites: 19M visitors 成人网站：1900万访问者 (= 71%) Personals Sites: 9M visitors　 社交网站：900万访问者 (= 32%) More details 更多内容 27 million year-old males who used the Internet in September spent an average of 32 hours per month online (in September, per person). 九月份使用过因特网的2700万18-34岁男性，平均每人每月在线时间为32小时。 This is 17 percent above than the 27 hours the average Internet user spent online during the month. 这比全体因特网用户本月平均在线时间27小时多出27%。 Males aged are also more engaged Internet users, voraciously consuming 3,370 pages per user in September 岁的男性属于较为狂热的网民，九月份每人贪婪地访问了3370个页面。

71 Platforms 平台 Enabling others 让他人帮你做
Example: Amazon’s “Mechanical Turk” ( 例子：亚马逊的“机械土耳其人”（ Application: CastingWords.com 应用：CastingWords.com

72 Current Situation: Market dominated by large players 现状一：大公司占据主导地位
Industry 行业 Company 公司 Ranking 行业排名 Market share 市场份额 On-Line Advertising 网络广告 Sina 新浪 NO.1 第一 20.4% Sohu 搜狐 NO.2 第二 13.9% Total Share 合计份额 34.3% On-Line Games 网络游戏 Shenda 盛大 18.96% Netease 网易 18.60% Zhengtu 征途 NO.3 第三 14.85% 52.41% IM 即时通讯 Tencent 腾讯 *94.0% MSN *35.6% 97.7% On-Line Shopping 网络购物 Taobao 淘宝 81.9% eBay 易趣 15.4% 97.3%

73 Current Situation：Big companies are dominating the market 现状一：大公司占据主导地位
Sources: 资料来源 Analysis Report on IM software 2006 from iresearch 艾瑞即时通讯类软件2006分析报告 Analysis Report on Market Share of On-line Advertisement 2006 from iresearch 艾瑞2006年中国网络广告市场份额报告 Report on China On-line Games of Q from Analysys International 易观2006年第4季度中国网络游戏市场季度监测 Report on On-line Shopping 2006 from China IntelliConsulting Corporation 正望中国2006年度网上购物调查报告

74 Mobile dominates in 2007 现状二：2007年手机占据主导地位
Internet users 互联网用户 Mobile phone users 手机用户 Ratio: Mobile to internet users 手机用户与互联网用户的比率 VoiP users 手机上网用户 PCs 安装的PC数量 137M 495M 3.6 to 1 17M 59.4M Internet users: China 2nd worldwide, with highest nr of users under 30 years worldwide 中国在互联网用户数量上排名第二，30岁以下的互联网用户数量则超过世界上其他任何国家 Mobile phone users: China highest worldwide Mobile games : 1.48 billion RMB in 2006 (up 50% over 2005) 年中国手机游戏市场规模为14.8亿元人民币，同比增长50% Mobile search increasing 但手机搜索正在逐步兴起，前景广阔。 Profit of wireless value-added business decreasing. 从互联网公司财报来看，无线增值业务收入为中国互联网公司带来的效益在下降。 Source：CNNIC statistic report of China internet development (19th ) 资料来源: 中国互联网络信息中心 (CNNIC) 19th中国互联网络发展状况统计报告 信息产业部2007年5月统计 数据

75 Revenues: Current and expected 目前和预计的收入
Dec 2006 截止2006年底 Forecast(2007) 预计 (2007年） Internet 互联网 Internet user 互联网用户 137M 1.37亿 Annual growth: 20 million users以每年2000万速度增加 Broadband user 宽带用户 91M 9100万 NA Mobile user 移动用户 400M 4.04亿 Average expense/month/user 单位用户月均支出 RMB170/month 每月170元 RMB (2007) 元（ 2007全年） Annual Revenue 行业整体年均收入 Revenues st Half 2007 年上半年 Search Engine 搜索引擎市场 RMB 1.15 billion（2007 1st Half） 11.5亿元 （2007 年上半年） RMB billion (2007) 亿元 （ 2007全年） Online Gaming 网络游戏 RMB 6.5 billion （73.5% than 2005) 65亿元（比2005年增长73.5% ） 30.2% （CAGR） Advertising 网络广告 RMB 4.66 billion 48.9% than 2005) 46.6亿元 （比2005年增长48.9% ） RMB billion (2007) 亿 （2007全年） 50%（ CAGR ）

76 Comparison of 70’s&80’s and 90’s 半人马和虚拟一代
70‘s& 80's 90's Main media 主媒介 TV 电视 Computer 电脑 Information 信息量 finite 有限的 infinite 无限的 Information Carrier 信息载体 paper and image 纸制和影像的 electronic 电子的 Information dissemination 信息传播 one-way 单向 two-way or multidimensional 双向乃至多维的 Material 物质 Ample 充裕 communication way 通讯手段 telephone 固定电话 IM and mobile phone IM和手机 friend cycle 朋友圈 family, reletives, schoolmates 家人、亲戚、同学 earth 地球人 relevance 关联方式 Realistic structure 现实结构 interest & hobby 兴趣爱好

77 Comparison of 70’s&80’s and 90’s 半人马和虚拟一代
70‘s& 80's 90's Learning institutions 学习场所 school 学校 search, BBS 搜索、BBS Express views 发表见解 speak on the class 课堂上发言 write Blog 写Blog comments source 意见来源 teacher and parents 老师和父母 all the people online 互联网上的所有人 Production 制作 guo families, play mud 过家家、玩泥巴 design product online 在网上设计产品 shopping 购物 virtual shopping 现实购物 online shopping 网上购物 payment 支付 cash 现金 Electronic Money 电子货币 entertainment content 娱乐内容 cartoons 动画片 online gaming 网络游戏 entertainment way 娱乐方式 watch 观看 role play 角色扮演

78 Fast growing 90’s generations 虚拟一代（90’s）快速成长
The Coverage of users between years old is the highest, reached to 38.8%, the future coverage of 90’s is expected higher 18～24岁间网民的普及率最高，达到38.8%，90’s的未来普及率将更高 Internet is the main medium for 90’s, and which is different from the generation who grew up with the TV 90’s以互联网为主媒介，不同于在电视为主媒介环境下成长的一代 Virtual is the reality, all is the now 虚拟就是现实，一切都是现在 Collaboration online after the disappearance of time and room 时间和空间消失后的网上协作生产 Self-centered perceptual consumption 自我为中心的感性消费 All media experienced communication 全媒体的体验式沟通

79 Top sites 最大的20个网站 Rank 排名 Web Site 网站 1 yahoo.com 2 msn.com 3
google.com 4 youtube.com 5 live.com 6 myspace.com 7 baidu.com 8 orkut.com 9 wikipedia.org 10 qq.com 11 megaupload.com 12 yahoo.co.jp 13 microsoft.com 14 hi5.com 15 facebook.com 16 sina.com.cn 17 blogger.com 18 rapidshare.com 19 ebay.com 20 friendster.com

80 Future III: The innovation of Web 2.0 is going on 未来三：中国Web2.0革新仍在继续
10 of the top 20 global websites are online community sites 在全球访问量最大的前20家网站中，社区/分享类网站基本占到一半 SNS, social networking sites SNS 社交网络网站 Focused on very few sites in the US… YouTube has 60% market share (160M users in May 2007) YouTube今年五月市场占有率达到60%（有16000万用户 MySpace has 80% of pageviews of community sites MySpace访问量占网络社区访问总量的80% Facebook is fastest growing (35M active users in Jul 2007, doubling every half year) Facebook发展最快（2007年7月有3500万在线用户，每半年翻一番） … but scattered in China … 但是中国的网络社区市场非常分散

81 Four dimension 四维度空间 Information 信息 Interactive 交互 Relationship 关系
Footprint 脚印 Notes 留言 Message 消息 IM 即时消息 Person 人 Video视频 Space 空间 Blog 博客 BBS 论坛 Audio音频 Picture 图片 Multi-dimension 多个维度 Text文字 Single group 单群体 Multi group 多群体 Interactive 交互 Multi- way 多样手段 Individual 孤立 One-dimension 单一维度 Global 全球脑 One-way 单一手段 Relationship 关系 2 D 二维 Avatar Online gaming 网游 SL Dating 交友 Business 商务 3D 三维 剧本化 Creation 创造 Role-play 扮演

82 Recent developments in social networking space in China 中国目前的社交网络空间发展
Baidu launched social search (similar to Yahoo Answers) 百度搜索社区初步成型（类似于Yahoo Answers） Baidu innovation: PostBa (2006) 百度创新：PostBa（2006年） Yahoo Answers itself inspired by Naver in Korea Yahoo Answers灵感来自于韩国的Naver Sina and Sohu add community and social networking aspects to their blogs 新浪/搜狐的博客正向社区和社交网络形态演化 More than a dozen clones of Second Life in China (July 2007) 中国有12多家企业在推出或正在推出类似Second Life的服务（2007年7月）

83 The Backdorm Boys