This study sought to determine the effects of personality traits on smartphone dependency and loneliness, controlling for the effects of students' self-perception towards instant messaging (IM) and email dependency, and compared them among social networks formed through face-to-face (FTF), IM and email. A total of 216 university students in Japan completed a questionnaire measuring their degree of personality traits (shyness and sociability), use of smartphones and computers, self-perceptions of IM/email dependency, and degree of smartphone dependency and loneliness. The results of factor analysis showed that students' self-perception of IM/email dependency was composed of the three factors of self-perception of text messages that Igarashi et al. (2008) indicated (namely, perception of excessive use, emotional reaction and relationship maintenance). The results of structural equation modeling showed that students' shyness and sociability influenced their self-perception of emotional reaction, which had the largest effects on smartphone dependency. Additionally, students' sociability led them to overuse IM/email, which helped reduce their loneliness but also led them to depend on smartphones more. Furthermore, female students' social networks via FTF and IM had positive effects on decreasing loneliness, while no similar effects for email were detected. The importance of distinguishing between the shy-sociable dependency (through the process of emotional reaction) and sociable dependency (through the process of excessive use) is discussed.

Public data collected or possessed by administrative agencies and subsequently released as Open Data is expected to bring about positive economic effects. The purpose of this study is to obtain findings contributing to the Open Data promotion in Japanese local governments. We conducted WEB questionnaire survey and obtained information networks of Open Data promotion in local governments. The network in the open data personnel had different characteristics from those of the WEB reference relationship network in the degree distribution. It shows those two networks have different structures. This result can be indicative that the regional binding plays an important role in the information network.