ネットワークコミュニティのリアリティ―ネットを介したコミュニケーションは本当に役に立つの？−

武田英明
国立情報学研究所
takeda@nii.ac.jp
http://www-kasm.nii.ac.jp/~takeda/
Hideaki Takeda / National Institute of Informatics

Network Communitiesz

New types of communities are emerging
 (Traditional) community: Bounded by real situations (Geographically, Socially, …)
 Fewer choices to form communities Network community or online community: Free from real situations
 Much more choices to form communities

Hideaki Takeda / National Institute of Informatics

1Frustration for Network Communitiesz

Network communities tend to be brittle and superficialWhy?

Lack of GroundednessWe often feel unrest for others and even ourselves when joining
network communities Neglect of Awareness Implicit/unconscious knowledge on others and ourselves Neglect of Orientation (Social or Individual Orientation)
 Explicit/conscious knowledge on others and ourselvesz

Hideaki Takeda / National Institute of Informatics

Regaining Groundedness
Outcropping awareness Avatar-like agent based community system
 Vesting corporeality by agent
z Outcropping orientation
 Bookmark-based community system Knowing others’ interest each other by bookmarkszHideaki Takeda / National Institute of Informatics

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TelMeA: Avatar‑Avatar‑like based Community Systemz

A system to realize asynchronous community where avatar-like agents areprovided for all participants

zFeaturesz

An avatar-like agent stands for identity of a participantCommunication close to face-to-face communication

Providing a field of community by multiple agents

Our Avatar-like AgentAn animated agent that canperform a sort of actions andbehavior

Composing action andbehavior by scripting

A scriptable agent that can beprogrammed easily by a scriptlanguage

RecordArticulation,
Explanation

Reaction,Response
Up LoadRetrieval

Discussion DBWebWeb-based Common Workspace
As a Field of the Community

Hideaki Takeda / National Institute of Informatics

TelMeAzz

Joint work with Toru Takahashi@NAIST/ATR MIC
Agent Design by ATR MIC
Hideaki Takeda / National Institute of Informatics

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TelMeA Use WWW pages as a field for communities
A field where agents move around and do actions
A field where users upload pages and images
Control Frame

Avatar-like AgentConversation List

Shared Page

Hideaki Takeda / National Institute of Informatics

ALAScriptz

All messages are written with a script language called ALAScript Simple tagged texts
 Scripts are generated by ALAScript editor
 Operating agents
 Choosing actions
 Writing messages

Hideaki Takeda / National Institute of Informatics

4Types of Actions
Identity

Interpersonal Representation＜##approach＞
approach agent_name
Move around a designated agent＜##actor＞
actor agent_name
Designate an agent to describe

Representation via Objects

Verbal Representation＜##open＞
open webpage_url
Open a designated WWW page＜##speak＞
speak comment_sentence
Utterance with voice and text＜##refer＞
refer image_id
Move around a designated image andmake the agent point to the image＜##think＞
think comment_sentence
Utterance only with text in balloon

Physical Representation

An Example of ALAScript＜##play＞
play animation_namePhysical behavior by animation＜##move＞
move point_on_the_screen
Move a designated position＜##actor>ToruTakahashi
actor>＜#approach#approach＞Hideaki
Takeda#approach＜#play#play＞Smile#play＜#speak#speak＞I
found such a nice page
#speak＜##open＞http://ai-www.aist-nara.ac.jp
open＜#speak#speak＞Better
than the last one．
#speak＜##refer＞img3@
ai-www.aist-nara.ac.jp
refer＜#speak#speak＞I
love it best in those pictures#speakHideaki Takeda / National Institute of Informatics

Analysis of a Test Use
Public in the institute for 9 daysz 7 people accessed the systemz 7 communities are createdz 18 messages are postedz<speak><play><move><approach><open><refer>
Total

352
53
4
1023424

Verbal Rep.
Physical Rep.
Interpersonal Rep.
Rep. Via Objects
Non‑Nonv
reRep.(total)
Non‑verbal

83.0%
13.4%
2.4%
1.2%
17.0%

Analysis of messages by phrase
Hideaki Takeda / National Institute of Informatics

5Subjective Evaluationz

Subjective Evaluation (5 Ranks；1: the most positive, 5: themost negative)
1. Evaluation of agents and fields: Perception, acceptability,and usefulness
15 questions: average 2.41
2. Evaluation of individual functions (Animation, moving etc.)
8 questions: average 1.50
3. Comparison with other communication tools
7 questions x 3 tools: average: 2.29

 Positive Evaluation for all aspects
Hideaki Takeda / National Institute of Informatics

Analysis of Subjective Evaluationz

Perception of agents: Avatar vs. Delegate
 Some users looks as avatar, others as delegate
 Most of users are consistent in perception of agents of others
and of themselves
 No significant effects to other evaluationsz

Acceptability and Usefulness Usefulness of agents > Acceptability of agents
 Acceptability of agent fields > Usefulness of agent fields
 Acceptability of agent fields > Acceptability of agentsz

Usability in comparison with other tools
 Joyful > usefulness, expressiveness > variety of information
Hideaki Takeda / National Institute of Informatics

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Regaining Groundedness
Outcropping awareness Avatar-like agent based community system
 Vesting corporeality by agent
z Outcropping orientation
 Bookmark-based community system Knowing others’ interest each other by bookmarks
zHideaki Takeda / National Institute of Informatics

PurposeGeneration of human network guiding individual information
activities An example
 I want to watch sports programs on TV. What yourrecommendation?
 Who and Whatz Shared Topics Network among Users (STN)z

Hideaki Takeda / National Institute of Informatics

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Our approachz

Combination of manual and automatic methods
 Identification of topic
Use of bookmark files as users’ knowledge

To overcome knowledge acquisition problem
 Discovery of inter-topic relations
Text analysis to calculate inter-topic relations

Hideaki Takeda / National Institute of Informatics

Knowledge Acquisition Problem
Difficulty to identify topics automatically Examples
 Learning: Webwatcher, Letizia
 Categorization: Webmate
 Weakness of text analysis methods
 “Persistence of interest” hypothesisz Bookmark files as users’ knowledge Bookmark structures are results of implicit/explicit efforts
to organize their informationz

Hideaki Takeda / National Institute of Informatics

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Bookmarks as Knowledgez

A bookmark folderz

URLs in a bookmark folder= A topic interested by the user

UserFolder(topic)x

WWW page(informationon the topic)= Examples of the topic
2

1
agb

Shared Topics Networkcf5
z

4ed3

yBookmark (person’s interest)
Hideaki Takeda / National Institute of Informatics

kMedia Interface

Browser
window

SharedTopics
NetworkBookmark withrecommendation
Hideaki Takeda / National Institute of Informatics

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Bookmark with recommendation
zTwo pages are related
Each page is a recommended page to the otherAcademic Related

Lab. in Universities

Yamada Lab.
AI Meeting RoomThe original data
Recommended data

Hideaki Takeda / National Institute of Informatics

Discovery of topic relations
Common relations
 (search, IR), (academia, research-related)
 similar but words themselves are differentz Un-common relations…(Unix, academia)
computer-related Speciality of theresearch-related
communityz

BsearchA

Information
retrievalacademiaC

Hideaki Takeda / National Institute of Informatics

10Discovery of relationship among people

What are common topics with others?
z Who is good at this topic?
zcomputer-related
research-related

searchB

researchresearchA

Information
retrievalunixacademia

CHideaki Takeda / National Institute of Informatics

Validity of recommended pages
Validity of page relations
GoodRank 5

Rank 4

Rank 3

Rank 1
BadRank 2

User A２９３０２７７７

User B

９４

８６

７３

User C

６６

９０８８

１８９

２０６

１８６

Total

Total

１８２

３４５

１８５

７５

５１３８８

１２２４５４

３５０３７９Validity of topics relations
GoodRank 5

Rank 4

Rank 3

BadRank 1

Rank 2

Total

User A

3320210User B

33220

10

User C

20100386522Total

Hideaki Takeda / National Institute of Informatics

11Summary
Searching a new type of “reality” for communities
 Free from real constraints
 But grounded on our implicit/explicit knowledgez Two systems are proposed TelMeA: Regaining corporeality
 kMedia: Regaining orientation for others and ourselves
z Future Directions
 More discussion on “Identity of persons in network”
 Grounded Virtual Characters on the Network Grounded Virtual Fields on the Networkz

Hideaki Takeda / National Institute of Informatics

体験モードと内省モード
思考の二つのモード (D.A.Norman)
 体験モード：物語的、習慣的、感覚的 内省モード：論理的、熟考的、概念的z 両者が適当にバランスすることが重要
z 情報技術で体験モードを支援することは容易 新しい体験モードの提供
z では内省モードは？
 考えることは自分でしかできない 自ら考えさせるモードへのスムーズな移行
zHideaki Takeda / National Institute of Informatics

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Mind Heap
文脈情報を利用した連想知識構造の構築と提示•アプローチアプローチ
ユーザが明示的に入力した知識のみならず、ユーザが入力しなかった暗黙的な前提知識暗黙的な前提知識の暗黙的な前提知識利用を考える。

•HTMLブラウザをインターフェースとして、連想知識構造を構築

知識を入力したときに表示されていたHTMLファイルを解析することによって、知識の周辺に付随する文脈情報にアクセスすることが可能。
→こうした文脈情報をも含めて、連想知識構造を構築する。

Hideaki Takeda / National Institute of Informatics

Hideaki Takeda / National Institute of Informatics

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