The purpose of this research is to clarify the factors that promote creation of new outcomes through co-creation activities. The target of this research was Special Interest Group on Crowd Co-Creation Intelligence at The Japanese Society for Artificial Intelligence. The feature of this group is to support creation of co-creation project and to promote activities by combining the academic workshop and social media. The following four data were analyzed; (a) Result of questionnaire conducted after academic workshops, (b) Log data of social media, (c) The number of new outcomes generated by co-creation activities, (d). Existence of relationships before academic workshop. Each data of (a) to (d) were aggregated for each co-creation project, and Spearman's rank correlation coefficient was calculated. As a results, the following three findings were obtained; 1. Promoting the sharing of participants' activities and interests in the academic workshop activate the number of discussion on social media and increase the number of outcomes generated through co-creation projects, 2. As the number of positive feedback on user activities on social media increases, the number of comments and progress reports on social media increase, as a results outcomes generated through co-creation projects increase, 3. Supporting the activation of discussions on social media increases the number of outcomes generated by co-creation projects.

In this paper, we propose methods for extracting social issues and missions from Web content like news articles. The purpose of this study is to solve the shortage of resources such as human resources of civil society organizations such as NPOs. Therefore, it is necessary for citizens to sympathize with the issues that NPO organizations want to solve. For this purpose, information extracted with reference to Golden Circle is defined, and extraction is automatically performed on the Internet by using machine learning. In this paper, we describe a technique for that purpose.

We have developed a plugin for QGIS to find an optimal path to support running the on-demand traffic service in Sanyo-Onoda city. In previous research, we re-designed the user-interface of the plugin in order to develop usability. We reviewed the re-designed user-interface with staff from the Sanyo-Onoda city hall who are in charge of the on-demand traffic service. Then, we concluded that the improvement made plugin usage easier, but still users have to set up factors which they do not need to do, such as map layer data and setting for pathfinding. Therefore, in this research, we design the wizard that simplifies the usage of the plugin and additional functions that support the wizard. As an intermediate evaluation, we prototyped the wizard with minimum required functions to find an optimal path and reviewed the usability of the wizard with the staff from the city hall. We concluded that the design of the wizard is exceptional though we need some more adjustment.