Social Attention Management in Online Community using Artificial Agents

Social Attention Management in Online Community using Artificial

AgentsNicolas Maisonneuve, Research Associate

Centre for Advanced Learning Technologies, INSEAD

Context: European research project www.atgentive.com

2008

Social translucence design

Social translucence design = Design knowledge management system to emphasize the social aspect

(Erickson et al. (2002). “Social translucence: designing social infrastructures that make collective activity visible”)

Why is emphasizing the social aspect important?Change of the user’s perception: from a repository of

resources to a community of peopleEmergence of social mechanisms (trust , affinity) Increase of the participation (main problem in Knowledge

Management)

Social translucence design

Approach 1: Multi Agent System Goal: Detecting and regulating different {collective,indivudual} behavioural scenarios (1 agent = 1 scenario)Agent behavior:

1- Observing the community’s activity2- Detecting a given activity pattern:

- Basic pattern: (e.g. the creation of a response) - More complex pattern: (a burst of activity)

3-Intervention/Recommending: a message with a recommendation is sent to the given user(s)

Objective: To help users to better perceive/understand what happens within the community

Process

A2A1A3

1/ Community Activity (reading, tagging, voting, exchanging knowledge)

4/ Raising of awarenessUsers are aware of bad behavior/hidden collective activity

Activity visible via RSS 2/ External Artificial Agents observe the activity

3/ When an agent detects a given activity pattern, it recommends an action by sending a message to the given user(s)

Agents related to the user’s state

• Agent1: Detecting if a new user is registered:

Msg sent to the user: “Look at the presentation of the community platform”,

Msg for the community to introduce the new user

• Agent 2: Detecting the degree of completeness of a user’s profile

Msg “complete yours skill in your profile”, “add a picture“

• Agent3: Detecting Inattentive user (low connection rate)

Emailing inattentive user with an activity report to attract their attention

Agents related to individual-individual interactions

• Agent4: Detecting if a user A check the user B profile:

Msg to the user B: “UserA viewed your profile”

• Agent5: Detecting if someone responded to User A’s messages

Msg to the user A: “User X responded to your message”

Examples of Basic Agents (1/2)

Agents related to the individual-collective interactions

• Agent 6: Detecting burst of collective activity to a owned resource:

msg to the owner of the resource: “Your profile/message was viewed by a high number of people (12 member(s)) [..]compared to the normal audience the last x days”

• Agent 7: Detecting special interest of a group compared to the collective

“2 members UserA, UserB viewed your profile more frequently than the others”

Examples of Advanced Agents (2/2)

Agents related to the social attention

Agent 8: Detecting change in the Attraction power/charisma of a user

“you’re loosing/gaining some audience compared to the last month”

Agent 9: Detecting if the diversity of the user’attention is low:

Msg to the user: “You don’t enough diversify your interest (focus on same people or same tags)?”

Social translucence design related to resources

Approach Resource/Tag as a memory of the social activity Showing the social activity related a resource or a Tag with the

resources to emphasize its social aspect using web widget

Diffusion in the community / audience of a resource - is my message well diffused in the community? - Is everybody aware about these posting?

Lifecycle of a resource - “is the resource dead?” - “is there a burst of activity now or these last days?”

Social aspect - who were the last readers? - who was interested by this document?

Web widget