Activate of community activities plays an important role in solving regional and national problems. In communities such as neighborhood associations, community activities sometimes carry out to enrich lives of members and improve their environment. Participation in community activities is supported by members having rights and responsibilities. However, there are few people who actually participate. That's because nonparticipants can obtain the same benefit with participants. Therefore, nomination of a leader who always participates in the activities and encourages the norm consciousness of the surrounding people is important to activate activities. In this research, we propose a community activity model introduced changes of a leader. We make community activity be activated by changing a leader.

Due to the recent trend of the Social Network and the increase in the number of academic papers published in the world, attributed networks consisting of relationships between objects such as humans and the papers are becoming huge. Therefore, various studies for clustering the attributed networks into some sub-networks are actively conducted. When clustering the attributed networks with the spectral clustering, the accuracy of the spectral clustering is greatly affected by quality of similarity matrices representing similarities between the objects. In this study, we aim to improve the accuracy by refining the matrices before applying the matrices to the spectral clustering. Furthermore, we verify practicability of our proposed method comparing accuracies of the spectral clustering with similarity matrices before and after refining.

Recently with the help of artificial intelligence (AI) in business sectors, innovative manufacturing methods are emerging. This study focuses on how to select mergers and acquisitions (M&A) partners automatically from transaction networks because transaction networks are important sources for business partner selection. We calculated betweenness centrality of and shortest path lengths between M&A pairs and found concentration intervals. From these results, we provide insights to M&A theory and practice.