• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.69-92
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• 2015

The explosion of social media data has led to apply text-mining techniques to analyze big social media data in a more rigorous manner. Even if social media text analysis algorithms were improved, previous approaches to social media text analysis have some limitations. In the field of sentiment analysis of social media written in Korean, there are two typical approaches. One is the linguistic approach using machine learning, which is the most common approach. Some studies have been conducted by adding grammatical factors to feature sets for training classification model. The other approach adopts the semantic analysis method to sentiment analysis, but this approach is mainly applied to English texts. To overcome these limitations, this study applies the Word2Vec algorithm which is an extension of the neural network algorithms to deal with more extensive semantic features that were underestimated in existing sentiment analysis. The result from adopting the Word2Vec algorithm is compared to the result from co-occurrence analysis to identify the difference between two approaches. The results show that the distribution related word extracted by Word2Vec algorithm in that the words represent some emotion about the keyword used are three times more than extracted by co-occurrence analysis. The reason of the difference between two results comes from Word2Vec's semantic features vectorization. Therefore, it is possible to say that Word2Vec algorithm is able to catch the hidden related words which have not been found in traditional analysis. In addition, Part Of Speech (POS) tagging for Korean is used to detect adjective as "emotional word" in Korean. In addition, the emotion words extracted from the text are converted into word vector by the Word2Vec algorithm to find related words. Among these related words, noun words are selected because each word of them would have causal relationship with "emotional word" in the sentence. The process of extracting these trigger factor of emotional word is named "Emotion Trigger" in this study. As a case study, the datasets used in the study are collected by searching using three keywords: professor, prosecutor, and doctor in that these keywords contain rich public emotion and opinion. Advanced data collecting was conducted to select secondary keywords for data gathering. The secondary keywords for each keyword used to gather the data to be used in actual analysis are followed: Professor (sexual assault, misappropriation of research money, recruitment irregularities, polifessor), Doctor (Shin hae-chul sky hospital, drinking and plastic surgery, rebate) Prosecutor (lewd behavior, sponsor). The size of the text data is about to 100,000(Professor: 25720, Doctor: 35110, Prosecutor: 43225) and the data are gathered from news, blog, and twitter to reflect various level of public emotion into text data analysis. As a visualization method, Gephi (http://gephi.github.io) was used and every program used in text processing and analysis are java coding. The contributions of this study are as follows: First, different approaches for sentiment analysis are integrated to overcome the limitations of existing approaches. Secondly, finding Emotion Trigger can detect the hidden connections to public emotion which existing method cannot detect. Finally, the approach used in this study could be generalized regardless of types of text data. The limitation of this study is that it is hard to say the word extracted by Emotion Trigger processing has significantly causal relationship with emotional word in a sentence. The future study will be conducted to clarify the causal relationship between emotional words and the words extracted by Emotion Trigger by comparing with the relationships manually tagged. Furthermore, the text data used in Emotion Trigger are twitter, so the data have a number of distinct features which we did not deal with in this study. These features will be considered in further study.

• Journal of Korean Society of Archives and Records Management
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• v.1 no.1
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• pp.69-94
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• 2001

The purpose of this paper is to provide an overview of the current status of the records management science education in Japan, and to examine the implications of the rapid growth of this filed while noting some of its significant issues and problems. The goal of records management science education is to improve the quality of information services and to assure an adequate supply of information professionals. Because records management science programs prepare students for a professional career, their curricula must encompass elements of both education and practical training. This is often expressed as a contrast between theory and practice. The confluence of the social, economic and technological realities of the environment where the learning takes place affects both. This paper reviews the historical background and current trends of records management science education in Japan. It also analyzes the various types of curriculum and the teaching staff of these institutions, with focus on the status of the undergraduate program at Surugadai University, the first comprehensive, university level program in Japan. The Faculty of Cultural Information Resources, Surugadai University, a new school toward an integrated information disciplines, was opened in 1994, to explore the theory and practice of the management diverse cultural information resources. Its purpose was to stimulate and promote research in additional fields of information science by offering professional training in archival science, records management, and museum curatorship, as well as librarianship. In 1999, the school introduced a master program, the first in Japan. The Faculty has two departments and each of them has two courses; Department of Sensory Information Resources Management; -Sound and Audiovisual Information Management, -Landscape and Tourism Information Management, Department of Knowledge Information Resources Management; -Library and Information Management, -Records and Archives Management The structure of the entire curriculum is also organized in stages from the time of entrance through basic instruction and onwards. Orientation subjects which a student takes immediately upon entering university is an introduction to specialized education, in which he learns the basic methods of university education and study, During his first and second years, he arranges Basic and Core courses as essential steps towards specialization at university. For this purpose, the courses offer a wide variety of study topics. The number of courses offered, including these, amounts to approximately 150. While from his third year onwards, he begins specific courses that apply to his major field, and in a gradual accumulation of seminar classes and practical training, puts his knowledge grained to practical use. Courses pertaining to these departments are offered to students beginning their second year. However, there is no impenetrable wall between the two departments, and there are only minor differences with regard requirements for graduation. Students may select third or fourth year seminars regardless of the department to which they belong. To be awarded a B.A. in Cultural Information Resources, the student is required to earn 34 credits in Basic Courses(such as, Social History of Cultural Information, Cultural Anthropology, History of Science, Behavioral Sciences, Communication, etc.), 16 credits in Foreign Languages(including 10 in English), 14 credits on Information Processing(including both theory and practice), and 60 credits in the courses for his or her major. Finally, several of the issues and problems currently facing records management science education in Japan are briefly summarized below; -Integration and Incorporation of related areas and similar programs, -Curriculum Improvement, -Insufficient of Textbooks, -Lack of qualified Teachers, -Problems of the employment of Graduates. As we moved toward more sophisticated, integrated, multimedia information services, information professionals will need to work more closely with colleagues in other specialties. It will become essential to the survival of the information professions for librarians to work with archivists, record managers and museum curators. Managing the changes in our increasingly information-intensive society demands strong coalitions among everyone in cultural Institutions. To provide our future colleagues with these competencies will require building and strengthening partnerships within and across the information professions and across national borders.