Enterprise 2.0: turning consumer-driven Web 2.0 technologies into business value, Qi Lu,Yahoo
description
Transcript of Enterprise 2.0: turning consumer-driven Web 2.0 technologies into business value, Qi Lu,Yahoo
Unleashing the Power of Collective Intelligence
NASSCOM 2008Mumbai, India
2
Agenda
• From Web 2.0 to Enterprise 2.0 • SLATES in Actions
– Flickr– Search & Social Search
• Enabling technologies • Emerging opportunities
User Generated
Content
Social Network
Wisdom of Crowds
Architecture of Participation
The Web 2.0 trends on the consumer Internet…
4
Web 2.0 Consumer Dynamics
1 creators
10 synthesizers
100 consumers
2 creators
4 synthesizers
8 consumers
Moving beyond “users”…
5
Web 2.0 Consumer Dynamics
100% creators
100% synthesizers
100% consumers
6
Happenstance artistes…
Anyone with a ________ is now a ________
keyboardcamera
iPodbrowser
authorphotographerdeejaypublisher
7
Enterprise 2.0
• The SLATES platform– Search– Links– Authoring– Tags– Extensions– Signals
• Business value driver:– harnessing collective intelligence
8
Flickr: A Pictorial view of SLATES in Acton
9
What makes Flickr special?
1. User Generated Content
Content not licensed from providers such as Corbis or Getty, but rather contributed by users.
10
What makes Flickr special?
2. User Organized Content
Content is tagged, described, organized, discovered, etc. not by “editors” but by the users themselves.
11
What makes Flickr special?
3. User Distributed Content
Flickr achieved distribution across the internet, not through “business deals” per se, but rather through the Flickr community which distributed Flickr content on 3rd-party blogs.
12
What makes Flickr special?
4. User Developed Functionality
Flickr exposed APIs (PHP, Perl, etc.) that allowed the community of developers to build against the Flickr platform.
13
What drives values in Flickr
• SLATES in actions– Search: the nexus that ties everything together– Authoring: ride the wave of ubiquitous of digital camera– Links: groups and social networks– Tags:
• Enabling text search• Geo tagging: the eyes of the world
– Extension• Interestingness algorithm • Scalable publication platform
– Signals: photo streams
14
Socialization of search: a historical view of SLATES in Search
Webmasters
<A>Engineers
& Scientists
Users
Alpha ChipSurfers
Enabling TechnologiesRight Incentives
Critical Mass
Thousandsof Newsgroups
Millionsof Web Sites
Trillionsof Knowledge
Artifacts
Usenet / Newsgroups
Google / Inktomi
Y! Answers /Delicious
Y! Directory / Altavista
Tens of Billionsof Web Docs
Link-Based AlgorithmsInfrastructure Scale
Source
Technology
Magnitude
Product
Better Search through People: The Yahoo! Answers example
16
Knowledge Search, 2003 in Korea
17
Naver
0
50,000,000
100,000,000
150,000,000
200,000,000
250,000,000
300,000,000
350,000,000
400,000,000O
ct-0
2
Jan-
03
Mar
-03
May
-03
Aug
-03
Oct
-03
Dec
-03
Mar
-04
May
-04
Jul-0
4
Sep
-04
Dec
-04
Feb
-05
Apr
-05
Jul-0
5
Pag
e V
iew
s p
er W
eek
Knowledge Search
Amazing user adoption…
18
Taiwan design
19
US design
20
India Design
21
DJ’s ask for Answers as part of their show programming
Professionals quote Answers levels as credentials
Level 6 – Home & Garden
Celebs, thought leaders, give out urls for more on their views & knowledge
7
Local listings contain answers level credentials
Pop culture mentions Answers frequently and in the context of broader issues – not as a promotion
Answers becomes the epicenter of social debate and fact exchange around key issues & political events
Where will this lead?
Better search through people: The del.icio.us example
23
Social bookmarks
24
Organizing the best of the web
25
Keep up to date on what your network finds interesting
26
What drives values
• Harnessing the collective intelligence– Capture
• Original content• Meta data
– Organize• Computationally discern quality, topic aboutness, …
– Access • Seek• Discover
27
Enabling technologies
• Tables takes– Web-based applications– Back-end services– Text search engines
• Secret sauce– Data and metadata– Modeling techniques – Large scale data-driven pattern discovery
28
Emerging opportunities
• New development approaches– Systems and applications
– Metrics and analytics
– Modeling techniques (algorithms, data mining….)
– Editorial operations
• New computing paradigm – DISC
• Open source grid computing, e.g., Hadoop
• Potential new vendor business opportunities – Software
– Services
– And beyond: e.g. partnership in joint discovery, R&D, ….
30