2012, Vol.29, No.4

Journal of the Korean Society for Information Management 2023 KCI Impact Factor : 1.31

pISSN : 1013-0799 / eISSN : 2586-2073
https://journal.kci.go.kr/kosim

This paper explores how interface environments have an influence on novice users’ performance in social virtual worlds (SVWs), which are emerging user-centric three-dimensional cyberspaces. Despite their early popularity, SVWs have experienced that numerous new users leave the cyberspaces soon before they become long-term users. One possible reason is that unfamiliar interfaces of SVWs can be a barrier to novice users’ adaptation of the technology. To understand a role of interfaces in the users’ assimilation of SVWs, we examine an impact of three interface factors (presence, affordance, and feedback) on performance which is regarded as a yardstick for users’ adaptation of SVWs. Forty participants were recruited and went through one-hour experimental sessions with seven tasks in Second Life; they were also asked to answer a questionnaire. Findings indicate that while affordance and feedback are significant factors influencing novice users’ performance, presence has no impact on their performance.

Recently libraries are experiencing an increasing number of difficult patrons because of the increase in the unemployment rate and the problem of mental health in their communities. The problem behaviours of difficult patrons have negative influence to other users and staff in the library. This seems closely associated with the decline in the quality of library services. Therefore, in this study, we developed a how-to-do-it manual for library staff to meet the aforementioned challenges and to enhance the overall quality of library services for both general users and difficult patrons.

Identifying citing sentences from article full-text is a prerequisite for creating a variety of future academic information services such as citation-based automatic summarization, automatic generation of review articles, sentiment analysis of citing statements, information retrieval based on citation contexts, etc. However, finding citing sentences is not easy due to the existence of implicit citing sentences which do not have explicit citation markers. While several methods have been proposed to attack this problem for English, it is difficult to find such automatic methods for Korean academic literature. This article presents a rule-based approach to identifying Korean citing sentences. Experiments show that the proposed method could find 30% of implicit citing sentences in our test data in nearly 70% precision.