Invited Talk, the First Workshop on Social Web and Interoperability,
the Fourth Asian Semantic Web Conference, Shanghai, December 7, 2009

Web of Documents, Web of People, andWeb of Creativity
Hideaki Takeda
takeda@nii.ac.jp
National Institute of Informatics
http://www.slideshare.net/takeda twitter: takechan2000

Joint work with Masahiro Hamasaki (AIST)
Hideaki Takeda / National Institute of Informatics

OutlineCommunity Web
 The
h modeld l forf Communityi Webb
 Social media
 Massively collaborative creation
 Social analysis of massively collaborative creation on a video
sharingh i siteit Conculsion

Hideaki Takeda / National Institute of Informatics

Apple, Inc. 2001
Hideaki Takeda / National Institute of Informatics

Information Circulation

Collect

GoogleCreateHTML editors

DonateWWW Servers

A new cycle is emerged!

Modified from Ben Shneiderman’s matrix of human activities (“Leonardo's Laptop”)
Hideaki Takeda / National Institute of Informatics

Information Circulation
Collect







C t
CreateDonateCollecting information
 Past: Libraries (limited just for books)
 Now: Google
Creating new information
 Past: creating from the scratch Now: creating
g with knowing
g other existingg information
Donating (publishing) information
 Past: Books, Journals, Mass Media (difficult part for ordinary people)
 Now: WWW
Hideaki Takeda / National Institute of Informatics

Internet as Information Activities

Internet

Hideaki Takeda / National Institute of Informatics

Changeg of Information Circulation SystemyPros: Changehoff power: fromflimitedli i d people
l to everyone
 Change of scale: from limited sources to unlimited sources
 Change of content: from qualified contents to everyday/everyone
contents
 Cons:C
 Lost of control
 EvenEcriminal
i i l informationi f
i can beb distributed
di ib d Lost of quality assurance

Hideaki Takeda / National Institute of Informatics

Information and Communication Activities

Two layers for our activities Information layer concerns how information is explicitly represented

and processed.

Information Layer
Collect

GoogleCreateDonateHTML editors

WWW Servers

something is missing
People!
Hideaki Takeda / National Institute of Informatics

Information and Communication Activities

Two layers for our activities Information layer concerns how information is explicitly represented

and processed.
 Communication layer concerns how relationship among people are organized
and maintained, which is potential route for information.
Information Layer
CreateCollect

DonateCommunication Layer
Collaborate
RelatePresent

Hideaki Takeda / National Institute of Informatics

Web as Communication
Web was created for research community
 It isi designedd i d mainly
i l forf datad andd informationi f
i exchangeh But it was soon used for communication too
Hideaki Takeda / National Institute of Informatics

Web as Communication
Typical Web Page
 Data andd informationi f
i on researchh Information for self introduction
 What’s new Links for colleagues
 Pages for groups
I f
Information
i for
f CommunicationCi i

My web page around 1996
Hideaki Takeda / National Institute of Informatics

Web as Communication
Typical Web Page
 Data andd informationi f
i on researchh Information for self introduction
 What’s new Links for colleagues
 Pages for groups

W bl (Bl )Weblog(Blog)

SNS
Wiki

I f
Information
i for
f CommunicationC
i i

Hideaki Takeda / National Institute of Informatics

Blog


Publishing information through identification over time

Information Layer
Collect

CreateDonateBlog (Blog tools9

Collaborate
RelatePresent

C
Communicationi ti Layer
L
Blog as Identity for individual

Blog as Identity for individual
Hideaki Takeda / National Institute of Informatics

SNS

Communication and publishing with personal network

Information Layer
Collect

CreateDonateCollaborate
RelatePresent

C
Communicationi ti Layer
L
Hideaki Takeda / National Institute of Informatics

wiki


Publishing with collaboration

Information Layer
Collect

CreateDonateCollaborate
RelatePresent

C
Communicationi ti Layer
L
Hideaki Takeda / National Institute of Informatics

Community WebExplicit support for both layers
Seamless support over two layers
Compound support over two layers: social media and its extension

Information Layer
Collect

CreateDonateSocial Media
Collaborate
RelateCommunication Layer

Present

Hideaki Takeda / National Institute of Informatics

Social MediaMedia consists of interaction among massive participants that are
widely distributed in the society.
society Via Social Network
 Via
Vi C
Communities
iti Examples
 MassM M
Mediadi (TV(TV, NewsN
Papers)P) …NoN
 Web … No in general BBS … YYes
 Blogs … Yes SNS … Yes Social tagging (Social bookmarking, Social news)… Yes Video Sharing … YesHideaki Takeda / National Institute of Informatics

Massivelyy Collaborative Creation
Creative activity through social media
 Examplesl BBS
 Q&A Sites (Yahoo! Answers[usa], Yahoo!Chiebukuro[jp], Naver
Knowledge iN [kr] …)
 Wikipedia
Wiki di Nico Nico Douga (Video sharing site) cf. Youtube
 Features
F Massive participation
 Generating new contents
 Interaction affects generation of new contents


Hideaki Takeda / National Institute of Informatics

Massivelyy Collaborative Creation (cont.)()


Different ways of affections by interaction to content creation
 Contents = Interactioni Interaction logs are used as contents
 Ex.) BBS, Q&A, etc
 Interaction influences content generation
 Content =/= Interaction
 Contents are generated under the influence of interaction
 Ex.) Flickr (images vs. tags), Youtube (movies vs. comments),
 Interaction is embedded into content generation
 Contents are created collaboratively
 Ex.) Wikipedia, Nico Nico Douga
Hideaki Takeda / National Institute of Informatics

What is “Nico Nico Douga” ?
 Nico Nico Douga is the one of the most popular video

sharing website in Japan The most interesting function is the direct overlaying of comments

on videosVideo

Overlaid
comments

Timeline view ofuser comments

Hideaki Takeda / National Institute of Informatics

Three types
yp of interaction on Nico Nico Dougag

Embedded interaction on the system
 Audiencediandd Audiencedi Sharing comments to same video
 Feeling pseudo synchronization

Users feel they watch a video together!

Emergentt Interaction
E
I tti
 Audience and Creators
 GoodG d ffeedback
db k ffor creators

Creators can get pin-point comments from users

 Creators
C t andd Creators
C t Audience become a creator

Hideaki Takeda / National Institute of Informatics

Hatsune Miku
Hatsune Miku is a version of singing synthesizer application
software (“vocaloid”)
 A user can make a singing song by giving a music note with lylic(piano roll) It has inspired many people to produce various music, picture, andvideo compositions


Hideaki Takeda / National Institute of Informatics

Example!!
p Title: Shooting star –short ver.- like an ending movie Creator: ussy
 URL: http://www.nicovideo.jp/watch/sm2030388
Hideaki Takeda / National Institute of Informatics

Re-using network on
Nico Nico Douga & Hatsune Miku

PictureMany pictures by many authors

Song
Shootingg star
Creator: minato

Song andMovie

3D modelShootingg star–complete ver.Creator: FEDis

Movie

Shooting star –short ver.like an ending movie
Creator: ussy
3D modeld l

3D Miku sings ‘01_ballede’Creator: kiokio

Song
melody… 3D PV ver1.50
Creator: ussy

melody…
Creator: mikuru396

Hideaki Takeda / National Institute of Informatics

Ap
part of network of re-usingg relationshipp amongg
creators using Hatune Miku on Nico Nico Douga

Our interests• What types of social network do creators have?
• How different types of creators interact to create
new content
t t throughthh their
th i social
i l network?
tk?
Our approach•We adopted a methodHideaki
of social
network
analysisTakeda/ National
Institute of Informatics

Findingsg
The creator’s network consists of a large and sparse component Different
iff
categories
i off creators havehdifferent
diff
roles
l in
i evolving
l i theh
network Creators’
C t ’ behaviorb h i isi similar
i il tot audiences’di’ one It likes Web2.0 style (A consumer is a creator!)
 SomeS
off communities
iti ini theth networktk are centralized,t li d andd havehspecific tags
 The characteristic ((“aa few popular creator and others
others”)) becomesstronger with time

Hideaki Takeda / National Institute of Informatics

Social Data of Hatsune Miku on Nico Nico Dougag36,709 videos with tag ’Hatsune Miku’ (31 May 2008)



Select 7,138 videos viewed more than 3,000 times
 Crawled during 1–5 June 2008
 The metadata include view times, uploaded date, uploader name,ttags,
andd a description
d
i ti



7,138
7
138 videos
idwere uploadedl d d byb 2,9112 911 uniqueicontributors
ib Note: We regard the uploader as the video creator On Nico Nico Douga, only the uploader is identified
 The uploader may not be the creator of the vide
Hideaki Takeda / National Institute of Informatics

How to make networks amongg moviesThe description of the movie often includes hyperlinks to other videos
showing trail of the video
video’ss creation
 On Nico Nico Douga, a creator often cites other videos if a sound,image,
g , or any
y ppart of another video is used as acknowledgementg

By tracing these hyperlinks, we generated a reference network of videos

Among the collected videos,
4,585 videos
idincludei l dhyperlinks in the description

Movie network 4,585 nodes (videos) 12,507 links (hyperlinks)
Hideaki Takeda / National Institute of Informatics

Videos’ network
nodes:
d 4,585
4 8edges: 12,507

Hideaki Takeda / National Institute of Informatics

How to make network amongg creators
We set a relation from creator of video A to creator of video B if
video A has link to video B It
I implies
i li thath CreatorC
A uses contents off CreatorC
B In this way, we generated a network among creators
Video’s network

A

B

video





Creators network 2,164 nodes (creators)
 4,368 links (relationships among creators)

video

Creator’s network

We regard this network as a social network of creators
Hideaki Takeda / National Institute of Informatics

Creators network
Creators’nodes: 2,164
edges: 4,368
Red: Songwriting
Blue: Song creation
Green: Illustration
Hideaki Takeda / National Institute of Informatics

Characteristics of the Creators Network•

The network is large and sparse The diameter of this network is 21
1000

Scale free network
 A few nodes (creators) gather
many links (citation)

100

10

1
1
0.1



10

100
y = 93.487x-1.214

Network centrality correlated to the number of play times
 Many cited videos are popular for users
 Creators’ behavior is similar to audiences’ one

Hideaki Takeda / National Institute of Informatics

1000Category of Creation Activity

We classifiedWl ifi d creativei activities
i i i related
l d to Hatsune
H
Mik into
Miku
i
four
f
categories:
 Songwritinggg Create an original song (lyrics and melody) Song creation
 Tune the software to create singing songs
 Illustration
 Draw pictures,
pictures textures,textures and create 3D models
 Produce many different scenes and facial expressions
 Editingg Choice videos and package them to one video

We classify creators semi-automatically using tags on videos
Hideaki Takeda / National Institute of Informatics

Relationshipp amongg categoriesgof creation
Many creators reuse Songwriting
creators’ contents

58

203
70

I
(Illustration)

Many Illustration
creators re
re-useuse
others’ contents

131

200

59

I&
C

102

65

149

58

W
W&C
(Songwriting )
75

W
&I

C
(Song creation)

241

68

149

unknown
152

53
W&I&
C

Hideaki Takeda / National Institute of Informatics

Communityy on Creators Network

We analyze the creators’ community
 The
h term ”creators’ community”
i means a tighti h group off nodesdwithin social network of creators
 We
W adoptd t NewmanNclusteringl t i tot detectd t t suchh communities
iti fromfthe social network of creators

Newman clustering generated 83 clusters (communities) from thesocial network of creators
 We especially investigated 7 clusters of which the size is greater than50
Hideaki Takeda / National Institute of Informatics

Hideaki Takeda / National Institute of Informatics

Structure of the biggest
gg clusters
Centralizaiton: an index of the centralityy of a network
 X^2: a degree of bias of tags in the clusters
 Key person: a node that has the most links




#
1
2
3
4
5
6
7

The number of links of the node should be more than 10 percent of the cluster

Size Centralization
161
4.293
144
0.080
118
5.257
95
1.868
91
5.897
90
7.055
79
5 164
5.164

X 2
X^2
Key person Majority
2130.5W
I
1747.3
I
1921.0
I&C
I, C
1857.7I
2799.9I
I
2333.7
W&C
C
1942 8
1942.8W
C
W: SongWriting, C: Song Creation, I:
Hideaki Takeda / National Institute of Informatics
Illustration

Structure of the biggest
gg clusters
Songwritinggg is often a keyy person,p, meaningg that Songwritinggg triggers
gg
creative activity
 Centered clusters often have a high degree of bias of tags




#
1
2
3
4
5
6
7

Centralized community often have community specific tags

Size Centralization
161
4.293
144
0.080
118
5.257
95
1.868
91
5.897
90
7.055
79
5 164
5.164

X 2
X^2
Key person Majority
2130.5W
I
1747.3
I
1921.0
I&C
I, C
1857.7I
2799.9I
I
2333.7
W&C
C
1942 8
1942.8W
C
W: SongWriting, C: Song Creation, I:
Hideaki Takeda / National Institute of Informatics
Illustration

Cluster 1
 Type Centered Key person
 Songwritinggg Majority
 Illustration

Hideaki Takeda / National Institute of Informatics

Cluster 2
 Type MessyKey person
 none Majority
 Illustration

Hideaki Takeda / National Institute of Informatics

Cluster 3
 Type Centered Key person

The keyy personpof this cluster introduced acharacter called ``Hachune Miku'' (aninfantilized version of the Hatsune Miku mascot)with leak Illustration &Song creation
 Majority
j y Illustration ,Song creation

Hideaki Takeda / National Institute of Informatics

Cluster 4• Type– Messy• Key person– None• Majority– Illustration

Hideaki Takeda / National Institute of Informatics

Cluster 5
 Type Centered Key person
 Illustration

The key person of thiscluster developed the tool toprogram complex
l motionsito
3D model Majority
 Illustration

Hideaki Takeda / National Institute of Informatics

Cluster 6
 Type Centered Key person
 Songwritinggg& Illustration
 Majority
j y Song creation

Hideaki Takeda / National Institute of Informatics

Cluster 7
 Type Centered Key person
 Songwritinggg Majority
 Song creation

Hideaki Takeda / National Institute of Informatics

Conclusion
Our use of Web is shifting
 Web
b off Documents: Linking
i ki documentsdisi New! Cool!
l Web of People: Linking people is New! Cool!
 Web of Creativity: Linking creative activity is New! Cool!
 The model “Community Web” model 3 Information activities and 3 Communication activities Creative activity is a composite of the above 6 activities
 Massively Collaborative Creation
 A new style of creation
 A natural extension of our use of web
 A full use of “community web” activities


Hideaki Takeda / National Institute of Informatics