Sen Yoshida

Socialware: multiagent systems for supporting network communities

COMMUNICATIONS OF THE ACM March 1999/Vol. 42, No. 3 55 There seems to be three major issues in the support of network communities. The first is how to bring people together, that is, how to link people with others and with communities that share similar interests [1, 7, 8]. Search engines or directory services for communities can partially help, but more sophisticated systems are needed. The second issue revolves around support for smooth communications [4], including support for visualizing and sharing common contexts, as well as s the Internet continues to grow, social activities through the

Shine: a peer-to-peer based framework of network community support systems

A discussion is presented on Shine, a framework of communication systems that support network communities. Shine provides a unified structural design approach to various network community support systems and enables them to share software components and cooperate with each other. Furthermore, Shine has a peer-to-peer architecture, which enables personal agents to form communities suitable for each user by exchanging data in a peer-to-peer style. These features of Shine are described and its effectiveness as a framework is verified by applying it to several systems.

Building a Network Community Support System on the Multi-agent Platform Shine

An increasing number of applications have been developed for supporting network communities. The authors have developed Community Organizer, which supports people in forming new network communities by providing places where people sharing interests and concerns can meet and communicate. The authors are also developing a platform named Shine to reduce the tasks needed to implement a variety of network community support systems such as Community Organizer. Shine has a multi-agent architecture because it is effective for network community support systems that have to adapt to dynamic changes in community organizations. This paper explains both Community Organizer and Shine, and then gives a description of building Community Organizer on top of Shine.

Incorporating content-based collaborative filtering in a community support system

Many systems have been developed to support people in forming communities and communicating with others in the communities. However, community support systems are not only concerned with community formation and communication. Namely, they give people the chance to make use of the communities for personal activities, e.g., they can use other members’ knowledge to select information items that are high in quality and conform to the user’s individual tastes. Collaborative filtering is a recommendation method that utilizes evaluations given by other users, and is therefore useful for users to obtain desired and relevant information items in a community. In this paper, we present an agent architecture of a community support system with a collaborative filtering method to recommend appropriate information items to users.

A platform for making network community support systems in a cooperative distributed architecture

There are an increasing number of applications that support communications in network communities. As the architecture of these applications, cooperative distributed agents are suitable for adapting to dynamic changes in community organizations. We are developing a platform named Shine as a common base for implementing network community applications in a cooperative distributed architecture. The paper describes the platforms significance, requirements, and design policy. We also show an example of building a network community support system on top of the platform.

Effectiveness of spatial representation in the formation of network communities: experimental study on community organizer

Abstract In this paper, we present and discuss Community Organizer, a system designed to support network communities. The main characteristic of Community Organizer is the use of spatial representations for the relationships among community members including the communications exchanged among these members. These spatial representations reflect the degree of closeness of interests and concerns among the members, and are intended to provide users with clues on how to form network communities. In order to investigate the effectiveness of the proposed spatial representations, we conducted experiments with two different versions of the software. One version offered meaningful spatial representations while the other version did not. The subjects who used the former software version felt a greater sense of ‘community’, enjoyed using the software more, and actively used it longer than the subjects using the latter software version (control condition). These results indicated that the proposed spatial representations are effective in supporting network community formation.