Mining Social Network of Conference Participants from the Web Yutaka Matsuo National Institute of Advanced Industrial Science and Technology (AIST) Aomi 2-41-6, Tokyo 135-0064, Japan y.matsuo@carc.aist.go.jp Hironori Tomobe University of Tokyo Hongo 7-3-1, Tokyo 113-8656, Japan tomobe@miv.t.u-tokyo.ac.jp Kˆ oiti Hasida AIST Aomi 2-41-6, Tokyo 135-0064, Japan hasida.k@carc.aist.go.jp Mitsuru Ishizuka University of Tokyo Hongo 7-3-1, Tokyo 113-8656, Japan ishizuka@miv.t.u-tokyo.ac.jp Abstract In a ubiquitous computing environment, it is desirable to provide a user with information depending on a user’s situation, such as time, location, user behavior, and social context. At conventions, such as academic conferences and exhibitions, where participants must register in advance, the social context of participants can be extracted from the Web using their names and affiliations without asking the partic- ipants many questions. In this paper, we attempt to extract the social network of participants from the Web, where a node represents a participant and an edge represents the relationship of two participants. Each edge is added using the number of pages retrieved by a search engine which in- clude both participants names. Moreover, each edge has a label such as “co-authors” and “members of the same project” by applying classification rules to the page con- tent. We show an example of the extracted network and make a preliminery evaluation. This network can be used in many information services, such as finding an appropri- ate introducer or negotiater, and who one shouldtalk to in order to efficiently expand his/her network. 1. Introduction In a ubiquitous computing environment [8], much infor- mation regarding users’ behavior can be obtained by a sen- sor network. We seek to provide users with personalized information depending on the situation: time, location, and user behavior. Especially at conventions such as academic conferences, the social context of each user is very impor- tant because the participants gather to experience new en- counters and exchange knowledge face-to-face. Assume a participant at a conference wants to make friends with researchers with similar interests near his cur- rent location. A future ubiquitous environment might de- tect the user’s location and recommend that the user talk to a certain person. However, without background knowledge about the social network, the system may recommend the user’s colleague or supervisor because they share the same interests. To make information services more “smart”, such knowledge is indispensable. By utilizing the knowledge about participants’ social network, many potential applications can be considered. Assume a user wants to talk to a certain person and wants someone to introduce her. With the help of social network knowledge, the system can determine who is appropriate to introduce her. Conversely, one can find the path from her- self to anyone with whom she might be talking. Another example might be efficient networking. A weak tie, which in social network theory is a connection between groups that don’t ordinarily interact, plays an important role in getting valuable information [3]. The system can suggest who may be a candidate for this weak tie, that is, one who shares sim- ilar interests, but is in a different social group. Also, if one wishes, one could find who he should make a tie with in order to become more centered in the network [2]. At academic conferences such as WI2003, a participant must register a profile (at least name and affiliation) prior to the conference. In such cases, it is reasonable to assume that we have a list of participants and time to gather in- formation about those participants from the Web. Referral Web [4] is a project to discover a social chain from an in- dividual to the target person from the Web; however, in our case, fortunately we have a list of names in advance, and try to discover the entire network structure among partici- pants from the Web. Digital services for social events are