The popularity of social networking sites (SNS) has facilitated communication between users. The usage of SNS helps users in their daily life in various ways such as sharing of opinions, keeping in touch with old friends, making new friends, and getting information. However, some users misuse SNS to belittle or hurt others using profanities, which is typical in cyberbullying incidents. Thus, in this study, we aim to identify profane words from the ASKfm corpus to analyze the profane word distribution across four different roles involved in cyberbullying based on lexicon dictionary. These four roles are: harasser, victim, bystander that assists the bully, and bystander that defends the victim. Evaluation in this study focused on occurrences of the profane word for each role from the corpus. The top 10 common words used in the corpus are also identified and represented in a graph. Results from the analysis show that these four roles used profane words in their conversation with different weightage and distribution, even though the profane words used are mostly similar. The harasser is the first ranked that used profane words in the conversation compared to other roles. The results can be further explored and considered as a potential feature in a cyberbullying detection model using a machine learning approach. Results in this work will contribute to formulate the suitable representation. It is also useful in modeling a cyberbullying detection model based on the identification of profane word distribution across different cyberbullying roles in social networks for future works.

Although fake news has been present in human history at any time, nowadays, with social media, deceptive information has a stronger effect on society than before. This article answers two research questions, namely (1) Is the dissemination of fake news supported by machines through the automatic con...

Open access is a paradigm whereby the electronic versions of scholarly publications are made freely accessible without any restrictions. It is actively promoted globally and is also promoted domestically in accordance with this global trend. However, there is a growing need to evaluate existing activities and to seek policies for the steady spread of open access. This study examines the necessity of switching to a national repository from existing institutional repositories through policy direction analysis of open repositories. We examined domestic open access policies by analysing various overseas cases and the situation in South Korea. Finally, we determined the validity of investment in a national repository by analysing its social and economic impacts using the modified Solow-Swan model. The main parameters for applying the modified Solow-Swan model were estimated, and the domestic research and development expenditure was predicted via a regression method. Then, we applied a range of rate of returns to research and development (10% to 50%) to various scenarios and examined the effects of increasing accessibility and efficiency by 1% to 10%. We found that the implementation of a national open access repository in South Korea would have a substantial impact (to the tune of 147 billion won), without considering the potential costs of such a repository. Based on the estimates of the social and economic impact of a national repository, the implementation of a national open access repository in South Korea is economically viable. Besides having beneficial social and economic impacts, a national repository is expected to enhance awareness of open access among Korean researchers and institutions.

While the body of research on metadata has grown substantially, there has been a lack of systematic analysis of the field of metadata. In this study, we attempt to fill this gap by examining metadata literature spanning the past 20 years. With the combination of a text mining technique, topic modeling, and network analysis, we analyzed 2,713 scholarly papers on metadata published between 1995 and 2014 and identified main topics and trends in metadata research. As the result of topic modeling, 20 topics were discovered and, among those, the most prominent topics were reviewed in detail. In addition, the changes over time in the topic composition, in terms of both the relative topic proportions and the structure of topic networks, were traced to find past and emerging trends in research. The results show that a number of core themes in metadata research have been established over the past decades and the field has advanced, embracing and responding to the dynamic changes in information environments as well as new developments in the professional field.

This study examined the mechanical engineering research output from India, Japan, and South Korea on different parameters including growth, collaboration indices, and activity index. The purpose of the study is to understand the overall development of mechanical engineering through analytical approaches applied on the scholarly outcome of the countries considered for the study. The study focuses on analysing the articles published by India, Japan, and South Korea, and is restricted to articles indexed in the Science Citation Index – Web of Science for the period 2000 to 2014. The ratios of number of paper to citations for India, Japan, and Korea are 20,836: 1,97,679; 24,494: 2,04,393; and 30,578: 2,66,902 respectively for the period 2000-2014. The findings show that there is a decline in Japanese publications in mechanical engineering, whereas other two countries have recorded an increasing trend. While India has tripled its publications in a span of 15 years, South Korea, on the other hand, has doubled its publications in the same span of time. There has been an increasing trend towards collaboration in almost all fields of science and technology. However, the extent of collaboration and their rate of growth varied for one subject to another, one branch to another branch of the same subject, and from one country to another country. The present study analyses the growth of research publications of the mechanical engineering domain including authorship distribution, collaboration indices, prominent journals, and activity index.