• Journal of the Korean BIBLIA Society for library and Information Science
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• v.32 no.1
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• pp.115-132
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• 2021

This study collected data on COVID-19 research papers published in international journals by Korean authors from WoS. Bibliographical analysis was performed on subject categories, institutions, funder distribution and so on. In addition, open access and journal review speed were also analyzed, which play an important role in facilitating academic publishing and distribution. The results showed that COVID-19-related papers published in international journals by Korean authors in 2020 included more papers on some specific fields, such as medicine, biology, and multidisciplinary. These researchers have published lots of papers not only in foreign journals but also in domestic English journals. 94% of papers were open access, and gold open access, which is available immediately after publication, was about 70% of the total. The COVID-19 orthopedic papers produced by Korean researchers were collected from PubMed and analyzed, and the average of review days was about 24 days. The analysis, including open access and review speed, showed that there has been an atmosphere of cooperation in the academic publishing ecosystem after the COVID-19 crisis. It would be desirable to continue this cooperation and address chronic problems in academic publishing system, such as promoting the publication of gold open access and reviewing efficiency.

• Journal of Information Management
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• v.39 no.4
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• pp.215-240
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• 2008

This paper presents a scientometric analysis of national patterns of research output and priorities in the sub-fields of Hepatitis covered in three bibliographic databases namely MEDLINE, CINAHL and IPA. The literature covered in three databases for the period 1984-2003 was considered. We have already discussed the Trends in the Growth of Literature on Hepatitis in our previous paper. Therefore in this paper only sub-fields analysis is presented. It has been found that the Hepatitis literature output has been grouped in 23 major sub-fields based on databases covered. It was found that there were high priorities for some of the sub-fields of Hepatitis research during 1984-1993. It was found that the research priority profile was more or less homogenous since majority of the sub-fields are showing either below or above average levels of priority profile. In the first phase of the research period covering from 1984-1993, there are high priorities in 10 sub-fields in USA followed by 9 in UK and 8 in Germany, 7 each in Canada, Russia and Netherlands. On the other hand, in the second phase (1994-2003) there are high priorities for 10 sub-fields in Germany, 9 in UK, 8 in USA, 7 each in Canada, Russia and Netherlands. In the productivity of Pediatrics sub-field, India is in the third position.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.24 no.4
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• pp.259-280
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• 2013

There has been a dramatic increase in the proportion of temporary employees in LIS fields, due to current trends of restructuring, automation, complete personnel systems, and complete wage systems. This research, therefore, conducted a survey exploring the current status and working environment of the temporary posts in LIS fields, in order to understand and direct the employment prospects of potential librarians. Results show that the average working period of more than half of temporary librarians are between 1-3 years. The total working period as a temporary librarian, including former experiences in their career, were evenly distributed between 1-5 years. Among those, being temporary often persisted, as 32% of temporary librarians stayed in their temporary status for more than 5 years. Second, temporary librarians perceived themselves as working the same hours as regular librarians, having independent or assistant tasks to regular librarians, and having a neutral or larger amount of tasks than regular librarians. Third, temporary librarians are employed and contracted from the work place, generally having contracts of less than 2 years or an open contract, which shows a serious level of job instability. Therefore, we should consider the following: proper remuneration for work of equal value, professional contractors, the supplementation of the total wage system and the number of public employees in the system as well as changing temporary positions to permanent positions and so on.

• Journal of the Korean Society for Library and Information Science
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• v.51 no.4
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• pp.99-120
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• 2017

In order to develop a semiautomatic support system that allows researchers concerned to efficiently analyze the technical trends for the ever-growing industry and market. This paper introduces a couple of Korean sentence generation models that can automatically generate definitional statements as well as descriptions of technical terms and concepts. The proposed models are based on a deep learning model called LSTM (Long Sort-Term Memory) capable of effectively labeling textual sequences by taking into account the contextual relations of each item in the sequences. Our models take technical terms as inputs and can generate a broad range of heterogeneous textual descriptions that explain the concept of the terms. In the experiments using large-scale training collections, we confirmed that more accurate and reasonable sentences can be generated by CHAR-CNN-LSTM model that is a word-based LSTM exploiting character embeddings based on convolutional neural networks (CNN). The results of this study can be a force for developing an extension model that can generate a set of sentences covering the same subjects, and furthermore, we can implement an artificial intelligence model that automatically creates technical literature.

• Journal of Korean Library and Information Science Society
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• v.51 no.1
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• pp.255-279
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• 2020

Recently, as the range of users utilizing open data has expanded from experts to students, and general citizens, the role of open data portals has changed. In the past, portals have neglected to increase data utilization through citizen participation by focusing on the role of simple data repository, but now they tend to focus on understanding, collaboration and sharing values so that users can actively use data. To meet these social trends, open data portals need to seek ways to improve user-centered services that can encourage citizen participation. The purpose of this study is to identify the main functions for citizen participation in open data portals, to analyze the current status of open data portal user services and to suggest ways to improve them. Through the literature research, we investigated the functions provided by portal services for citizen participation, deduced the types of user services, and analyzed open data portal user services. Furthermore, we suggested user-centered public data portal services improvement plans for citizen participation.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.141-156
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• 2013

Social media is a representative form of the Web 2.0 that shapes the change of a user's information behavior by allowing users to produce their own contents without any expert skills. In particular, as a new communication medium, it has a profound impact on the social change by enabling users to communicate with the masses and acquaintances their opinions and thoughts. Social media data plays a significant role in an emerging Big Data arena. A variety of research areas such as social network analysis, opinion mining, and so on, therefore, have paid attention to discover meaningful information from vast amounts of data buried in social media. Social media has recently become main foci to the field of Information Retrieval and Text Mining because not only it produces massive unstructured textual data in real-time but also it serves as an influential channel for opinion leading. But most of the previous studies have adopted broad-brush and limited approaches. These approaches have made it difficult to find and analyze new information. To overcome these limitations, we developed a real-time Twitter trend mining system to capture the trend in real-time processing big stream datasets of Twitter. The system offers the functions of term co-occurrence retrieval, visualization of Twitter users by query, similarity calculation between two users, topic modeling to keep track of changes of topical trend, and mention-based user network analysis. In addition, we conducted a case study on the 2012 Korean presidential election. We collected 1,737,969 tweets which contain candidates' name and election on Twitter in Korea (http://www.twitter.com/) for one month in 2012 (October 1 to October 31). The case study shows that the system provides useful information and detects the trend of society effectively. The system also retrieves the list of terms co-occurred by given query terms. We compare the results of term co-occurrence retrieval by giving influential candidates' name, 'Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn' as query terms. General terms which are related to presidential election such as 'Presidential Election', 'Proclamation in Support', Public opinion poll' appear frequently. Also the results show specific terms that differentiate each candidate's feature such as 'Park Jung Hee' and 'Yuk Young Su' from the query 'Guen Hae Park', 'a single candidacy agreement' and 'Time of voting extension' from the query 'Jae In Moon' and 'a single candidacy agreement' and 'down contract' from the query 'Chul Su Ahn'. Our system not only extracts 10 topics along with related terms but also shows topics' dynamic changes over time by employing the multinomial Latent Dirichlet Allocation technique. Each topic can show one of two types of patterns-Rising tendency and Falling tendencydepending on the change of the probability distribution. To determine the relationship between topic trends in Twitter and social issues in the real world, we compare topic trends with related news articles. We are able to identify that Twitter can track the issue faster than the other media, newspapers. The user network in Twitter is different from those of other social media because of distinctive characteristics of making relationships in Twitter. Twitter users can make their relationships by exchanging mentions. We visualize and analyze mention based networks of 136,754 users. We put three candidates' name as query terms-Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn'. The results show that Twitter users mention all candidates' name regardless of their political tendencies. This case study discloses that Twitter could be an effective tool to detect and predict dynamic changes of social issues, and mention-based user networks could show different aspects of user behavior as a unique network that is uniquely found in Twitter.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.179-200
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• 2019

Word-of-mouth (WoM) is defined by consumer activities that share information concerning consumption. WoM activities have long been recognized as important in corporate marketing processes and have received much attention, especially in the marketing field. Recently, according to the development of the Internet, the way in which people exchange information in online news and online communities has been expanded, and WoM is diversified in terms of word of mouth, score, rating, and liking. Social media makes online users easy access to information and online WoM is considered a key source of information. Although various studies on WoM have been preceded by this phenomenon, there is no meta-analysis study that comprehensively analyzes them. This study proposed a method to extract major researches by applying text mining techniques and to grasp the main issues of researches in order to find the trend of WoM research using scholarly big data. To this end, a total of 4389 documents were collected by the keyword 'Word-of-mouth' from 1941 to 2018 in Scopus (www.scopus.com), a citation database, and the data were refined through preprocessing such as English morphological analysis, stopwords removal, and noun extraction. To carry out this study, we adopted main path analysis (MPA) and word co-occurrence network analysis. MPA detects key researches and is used to track the development trajectory of academic field, and presents the research trend from a macro perspective. For this, we constructed a citation network based on the collected data. The node means a document and the link means a citation relation in citation network. We then detected the key-route main path by applying SPC (Search Path Count) weights. As a result, the main path composed of 30 documents extracted from a citation network. The main path was able to confirm the change of the academic area which was developing along with the change of the times reflecting the industrial change such as various industrial groups. The results of MPA revealed that WoM research was distinguished by five periods: (1) establishment of aspects and critical elements of WoM, (2) relationship analysis between WoM variables, (3) beginning of researches of online WoM, (4) relationship analysis between WoM and purchase, and (5) broadening of topics. It was found that changes within the industry was reflected in the results such as online development and social media. Very recent studies showed that the topics and approaches related WoM were being diversified to circumstantial changes. However, the results showed that even though WoM was used in diverse fields, the main stream of the researches of WoM from the start to the end, was related to marketing and figuring out the influential factors that proliferate WoM. By applying word co-occurrence network analysis, the research trend is presented from a microscopic point of view. Word co-occurrence network was constructed to analyze the relationship between keywords and social network analysis (SNA) was utilized. We divided the data into three periods to investigate the periodic changes and trends in discussion of WoM. SNA showed that Period 1 (1941~2008) consisted of clusters regarding relationship, source, and consumers. Period 2 (2009~2013) contained clusters of satisfaction, community, social networks, review, and internet. Clusters of period 3 (2014~2018) involved satisfaction, medium, review, and interview. The periodic changes of clusters showed transition from offline to online WoM. Media of WoM have become an important factor in spreading the words. This study conducted a quantitative meta-analysis based on scholarly big data regarding WoM. The main contribution of this study is that it provides a micro perspective on the research trend of WoM as well as the macro perspective. The limitation of this study is that the citation network constructed in this study is a network based on the direct citation relation of the collected documents for MPA.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.2
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• pp.17-26
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• 2021

For the past half century, the Journal of the Korean Landscape Architecture has been leading the landscape architecture research and industry inclusively. In this study, abstracts of 1,802 articles were collected and analyzed with topic modeling and network analysis method. As a result of this paper, a total of 27 types of subjects were identified. Health and healing in the field of environmental psychology, garden and aesthetics, participation and community, modernity, place and placenness, microclimate, tourism and social equity also have been continued as important research area in this journal. Modernity, community and urban regeneration is hot topics and ecological landscape related topics were cold topics. Although there was a difference by subject, the variability of the research subjects appeared after the 2000s. In Network analysis, it shows that 'Park' is a representative keyword that can symbolize the journal, and 'landscape' is also important a leading area of the journal. Looking at the overall structure of the network, it can be seen that the journal conducts research on 'utilizing', 'using', and creating 'park', 'landscape', and 'space'. This study is meaningful in that it grasped the overall research trend of the journal by using topic modeling and network analysis of text mining.

• Journal of Information Management
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• v.42 no.4
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• pp.95-113
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• 2011

The new millennium with mystifying convergence of IT has opened new challenges to LIS profession. This has resulted to continuous skill development and lifelong learning, for capacity building in consonant with contemporary changes. The LIS profession in India has created several mechanisms to organize and conduct several skills development programmes through which professionals are continuously enabled to update their professional knowledge and skills, in practice and teaching. There is a good organizational infrastructure and identified areas related to the recent developmental trends and as such LIS professionals and educators have facilities for updating their knowledge at veritable levels and intervals. The paper has surveyed programmes conducted by different organizations at different levels and highlights the aspects of the organizational infrastructure and the emergent areas of applications in LIS teaching, research and professional practices in India. The selection of areas and subjects for various skill development programmes suggest the competencies acquired by the LIS professionals from India, and the empowerment of their professional knowledge can be of immense value to its neighbouring countries. The paper highlights the knowledge and competencies of the LIS professionals in India and the broad-based facilities available here which can be a model for those countries which are seeking to utilize the LIS human resources from this part of the sub-continent. The paper in this circumstance surveyed on the institutional infrastructure for skill developmental opportunities available in India which would meet such requirements within and to the countries outside in the South Asian region seeking its collaboration in such manpower development work.