• The Korean Journal of Archival Studies
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• no.76
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• pp.5-37
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• 2023

This study aimed to design an evaluation system applicable to permanent record management institutions, focusing on the Seoul Archives, in order to implement the reevaluation of permanent record management institutions. As a process for this, an area for evaluating evidence, administrative, and historical values was established and detailed evaluation factors were derived. In order to effectively apply the set evaluation factors, the evaluation procedure was designed by dividing them into three stages. In the first stage of law-based evaluation, long-term preservation was determined by identifying the position and legal form of policymakers that can be immediately evaluated according to clear standards. Records that have not been determined for long-term preservation were reorganized into evaluation factors, such as record management standards, official document classification tables, pledges, and policies, which are the second stage of business function-based evaluation, and then comprehensively applied to review the validity of long-term preservation of held records. In the second stage of evaluation, records that were not judged as long-term preservation were judged by applying historical events, cultural assets, and collection policies in the subject-based evaluation stage, which is the third stage of evaluation. The designed evaluation system can find significance in minimizing the arbitrariness reflected in the evaluation and increasing the efficiency of the evaluation, and it has been confirmed that it is possible to evaluate comprehensively reflecting the various contexts and values of the records. In addition, a re-evaluation system suitable for permanent records management institutions was established by combining balanced macro-evaluation and micro-evaluation.

• Journal of Service Research and Studies
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• v.13 no.1
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• pp.96-107
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• 2023

The objective of this study is to explore future issues that Chinese users, who have the highest mobile payment service usage rate in the world, will be most interested in. For this purpose, after collecting text data from a Chinese SNS site, it classifies major keywords into 4 types of future signals by using Keyword Emergence Map (KEM) and Keyword Issue Map (KIM). Furthermore, to understand the four types of signals in detail, it performs the qualitative analysis on text related to each signal keyword. As a result, it finds that the strong signal, which is rapidly growing in keyword appearance frequency during this research period, includes the keywords related to the daily life of Chinese people, such as buses, subways, and household account books. Additionally, it find that the signal that appears frequently now, but with a low increase rate, includes various services that can replace cash payment, such as hongbao (cash payment) and bank cards. The weak signal and latent signal, which appear less often than other two signals, includes the keywords related to promotion events or changes in service regulations. Its result shows that the mobile payment services greatly have changed user's daily life beyond providing convenience. Furthermore, it shows that, in the Chinese market, in which card payment is not common, the mobile payment services have the great potential to completely replace cash payment.

• Korean Journal of Culture and Social Issue
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• v.13 no.1
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• pp.1-41
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• 2007

This study examines factors that influence delinquent behavior among Korean adolescents using longitudinal analysis. A total of 1,012 students completed a questionnaire when they were Grade 6 and 739 students completed a follow-up questionnaire when they became Grade 9. Results of multiple regression analysis indicate that the following variables predicted delinquent behavior of Grade 9 students: Bullying, previous delinquency, experience of punishment, victimization, social efficacy, and moral disengagement. The above six variables have direct and mediating influence of delinquent behavior. Relational factors also influenced delinquent behavior. Social exclusion from friends reduce social efficacy, which increases victimization and which in turn increases bullying, leading to greater delinquency. Parental rejection, social exclusion from friends and hostility from teachers increase moral disengagement, which increases bullying, leading to delinquency. Low academic achievement increases the likelihood of being punished, which increases bullying, leading to delinquency. The results indicate that moral disengagement and social efficacy are mediating factors of delinquency and negative life-events (i.e., social exclusion from friends, rejection from teachers, hostility from parents and low academic achievement) increase the likelihood that Korean adolescents will engage in delinquent behavior. Implications of the results for future research are discussed.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.1-13
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• 2023

The widespread adoption of smartphones and advancements in internet technology have notably shifted content consumption habits toward video. This research aims to dissect the nature of videos posted on YouTube, the global video-sharing platform, to understand the characteristics of both produced and preferred content. For this study, dance was chosen as a specific subject from a variety of video categories. Data on YouTube videos associated with the term "dance" was compiled over three years, from 2019 to 2021. The investigation revealed a clear distinction between the types of dance videos frequently uploaded to YouTube and those that receive a high number of views. The empirical analysis of this study indicates a viewer preference for vlogs that provide insights into the daily lives of dance students, as well as for purpose-driven videos, such as those highlighting dance exam preparations or school dance events. Notably, the vlogs that attract the most attention are typically created by dance students at the college or secondary school level, rather than by professionals. Although the study was focused on dance, its methodologies can be applied to different subjects. These insights are expected to contribute to the development of a recommendation system that aids content creators in effectively targeting their productions.

• Land and Housing Review
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• v.15 no.3
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• pp.113-127
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• 2024

This study explores shifts in real estate investment sentiment using media reports from 2012 to 2022, segmenting the market dynamics into three distinct cycles based on housing and land transaction indices. Leveraging 54 BigKinds media sources, we investigates 3,387 headlines and 8,544 body texts using LDA topic modeling. The results show that the first cycle (2012-2015 ) centered on apartment pre-sales, where policy changes influenced sentiment but did not consistently affect investment decisions. The second cycle (2016-2018) was characterized by interest rate hikes and rising property prices in Seoul, resulting in significant fluctuations in transaction volumes. The third cycle (2019-2022) encompassed the effects of COVID-19, market instability, and policy failures, leading to distorted and weakened investment sentiment. Each cycle demonstrated that policies, interest rates, and economic events significantly shaped investor sentiment, as reflected in media reports.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.153-169
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• 2011

Today using Internet environment is considered absolutely essential for establishing corporate marketing strategy. Companies have promoted their products and services through various ways of on-line marketing activities such as providing gifts and points to customers in exchange for participating in events, which is based on customers' membership data. Since companies can use these membership data to enhance their marketing efforts through various data analysis, appropriate website membership management may play an important role in increasing the effectiveness of on-line marketing campaign. Despite the growing interests in proper membership management, however, there have been difficulties in identifying inappropriate members who can weaken on-line marketing effectiveness. In on-line environment, customers tend to not reveal themselves clearly compared to off-line market. Customers who have malicious intent are able to create duplicate IDs by using others' names illegally or faking login information during joining membership. Since the duplicate members are likely to intercept gifts and points that should be sent to appropriate customers who deserve them, this can result in ineffective marketing efforts. Considering that the number of website members and its related marketing costs are significantly increasing, it is necessary for companies to find efficient ways to screen and exclude unfavorable troublemakers who are duplicate members. With this motivation, this study proposes an approach for managing duplicate membership based on the social network analysis and verifies its effectiveness using membership data gathered from real websites. A social network is a social structure made up of actors called nodes, which are tied by one or more specific types of interdependency. Social networks represent the relationship between the nodes and show the direction and strength of the relationship. Various analytical techniques have been proposed based on the social relationships, such as centrality analysis, structural holes analysis, structural equivalents analysis, and so on. Component analysis, one of the social network analysis techniques, deals with the sub-networks that form meaningful information in the group connection. We propose a method for managing duplicate memberships using component analysis. The procedure is as follows. First step is to identify membership attributes that will be used for analyzing relationship patterns among memberships. Membership attributes include ID, telephone number, address, posting time, IP address, and so on. Second step is to compose social matrices based on the identified membership attributes and aggregate the values of each social matrix into a combined social matrix. The combined social matrix represents how strong pairs of nodes are connected together. When a pair of nodes is strongly connected, we expect that those nodes are likely to be duplicate memberships. The combined social matrix is transformed into a binary matrix with '0' or '1' of cell values using a relationship criterion that determines whether the membership is duplicate or not. Third step is to conduct a component analysis for the combined social matrix in order to identify component nodes and isolated nodes. Fourth, identify the number of real memberships and calculate the reliability of website membership based on the component analysis results. The proposed procedure was applied to three real websites operated by a pharmaceutical company. The empirical results showed that the proposed method was superior to the traditional database approach using simple address comparison. In conclusion, this study is expected to shed some light on how social network analysis can enhance a reliable on-line marketing performance by efficiently and effectively identifying duplicate memberships of websites.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.77-92
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• 2014

Recently, numerous documents including unstructured data and text have been created due to the rapid increase in the usage of social media and the Internet. Each document is usually provided with a specific category for the convenience of the users. In the past, the categorization was performed manually. However, in the case of manual categorization, not only can the accuracy of the categorization be not guaranteed but the categorization also requires a large amount of time and huge costs. Many studies have been conducted towards the automatic creation of categories to solve the limitations of manual categorization. Unfortunately, most of these methods cannot be applied to categorizing complex documents with multiple topics because the methods work by assuming that one document can be categorized into one category only. In order to overcome this limitation, some studies have attempted to categorize each document into multiple categories. However, they are also limited in that their learning process involves training using a multi-categorized document set. These methods therefore cannot be applied to multi-categorization of most documents unless multi-categorized training sets are provided. To overcome the limitation of the requirement of a multi-categorized training set by traditional multi-categorization algorithms, we propose a new methodology that can extend a category of a single-categorized document to multiple categorizes by analyzing relationships among categories, topics, and documents. First, we attempt to find the relationship between documents and topics by using the result of topic analysis for single-categorized documents. Second, we construct a correspondence table between topics and categories by investigating the relationship between them. Finally, we calculate the matching scores for each document to multiple categories. The results imply that a document can be classified into a certain category if and only if the matching score is higher than the predefined threshold. For example, we can classify a certain document into three categories that have larger matching scores than the predefined threshold. The main contribution of our study is that our methodology can improve the applicability of traditional multi-category classifiers by generating multi-categorized documents from single-categorized documents. Additionally, we propose a module for verifying the accuracy of the proposed methodology. For performance evaluation, we performed intensive experiments with news articles. News articles are clearly categorized based on the theme, whereas the use of vulgar language and slang is smaller than other usual text document. We collected news articles from July 2012 to June 2013. The articles exhibit large variations in terms of the number of types of categories. This is because readers have different levels of interest in each category. Additionally, the result is also attributed to the differences in the frequency of the events in each category. In order to minimize the distortion of the result from the number of articles in different categories, we extracted 3,000 articles equally from each of the eight categories. Therefore, the total number of articles used in our experiments was 24,000. The eight categories were "IT Science," "Economy," "Society," "Life and Culture," "World," "Sports," "Entertainment," and "Politics." By using the news articles that we collected, we calculated the document/category correspondence scores by utilizing topic/category and document/topics correspondence scores. The document/category correspondence score can be said to indicate the degree of correspondence of each document to a certain category. As a result, we could present two additional categories for each of the 23,089 documents. Precision, recall, and F-score were revealed to be 0.605, 0.629, and 0.617 respectively when only the top 1 predicted category was evaluated, whereas they were revealed to be 0.838, 0.290, and 0.431 when the top 1 - 3 predicted categories were considered. It was very interesting to find a large variation between the scores of the eight categories on precision, recall, and F-score.

• International Area Studies Review
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• v.22 no.4
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• pp.55-75
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• 2018

In China, different from the private enterprises or the locally-administered state enterprises, central state-owned enterprises generally spread over cornerstone industry which is greatly influenced by the public policy, which results in the objective existence of government influence in their productive activities. As the strategic resource, listed companies controlled by central state-owned enterprises, mostly distributed in the lifeblood and security of key industries. Therefore, listed companies controlled by central state-owned enterprises' governance efficiency play an important role in optimal allocation of state-owned assets, improve capital operation, improve the return on capital, and maintain state-owned assets safety. As the immune systems of national governance, the government audit strengthen the supervision of listed companies controlled by central state-owned enterprises in case of the loss of state-owned assets and significant risk events occur, to ensure that the value of state-owned assets. As an important component of national governance, government audit produced in entrusted with the economic responsibility of public relationship. Government audit can play an important role in maintaining financial security and corruption, and also improve listed company's accounting stability and transparency. While government audit can improve governance efficiency and maintain state-owned assets safety, present literature is scarce. Under the corporate governance theory and the economical responsibility theory, the thesis select data from 2010-2017 to verify the relationship between government audit and listed companies controlled by central state-owned enterprises' corporate performance. Results show that listed companies controlled by central state-owned enterprises are more likely to be audited by government of poor performance. Results also show that the government audit will have a promoting effect on listed companies controlled by central state-owned enterprises, and through to the improvement of the governance efficiency will enhance its companies' value. The results show that China's government audit has appealing role in accomplishing central state-owned enterprises to realize the business objectives and in promoting the governance efficiency.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.6
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• pp.31-42
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• 2021

The importance of startups and ventures in the Korean economy is growing. This study measured whether the start-up and venture ecosystem is growing, including the growth of startups and ventures. The startup and venture ecosystem consists of startups and ventures, investors, and government, which are the main actors of the 'ecosystem', and their movements were measured with 25 quantitative indicators. Based on the original data of the time series from 2010 to 2020, the startup and venture ecosystem index was calculated by applying weights through the comprehensive stock index method and AHP. In 2020, the startup and venture ecosystem grew 2.9 times compared to 2010, and the increase in the government index had a significant impact on growth. Also, the individual indicators that make up each index in 2020, the corporate index had the greatest impact on the growth of the number of 100-billion ventures, while the investment index had a recovery amount and the government index had a significant impact. Based on the original data, the startup and venture ecosystem index was analyzed by dividing it into ecosystems (startup ecosystem and venture ecosystem), industry by industry (all industries and manufacturing industry), and region (Korea and Busan). As a result, the growth of the startup ecosystem over the past decade has been slightly larger than that of the venture ecosystem. The manufacturing was lower than that of all industries, and Busan was lower than that of the nation. This study was intended to use it for the establishment and implementation of support policies by developing, measuring, and monitoring the startup and venture ecosystem index. This index has the advantage of being able to research the interrelationships between major actors, and anyone can calculate the index using the results of official statistical surveys. In the future, it is necessary to continuously update this content to understand how economic and social events or policy support have affected the startup and venture ecosystem.

• Journal of Korea Entertainment Industry Association
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• v.13 no.7
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• pp.87-98
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• 2019

This study sought to identify the impact of scenarios, capital, manpower (directors, actors), media promotion, oral communication, and recognition on the intention of watching movies, and to present marketing and policy implications to film producers for ways to revitalize their films. Therefore, the implications of this study are as follows: First, if you watch a movie with a friend or introduce a movie, you should set up a marketing strategy to promote the movie as a oral message to the people around you through double points and free admission at the 10th movie. It will also require the promotion of the scenario to be strengthened so that people around them can recognize it naturally. Second, film production companies will have to improve the quality of their movies by readjusting the distribution of capital in the event of capital investment. In addition, the movie should be encouraged by the oral publicity that the huge amount of capital has enhanced the quality of the movie, as well as pre-experience events to help the audience recognize it. Third, filmmakers will have to choose directors and actors who can digest novel and experimental material over the director's or actor's reputation. Fourth, the movie promotion company should set up strategies to cater to visitors through a contest for ideas for promoting visitors, which can arouse interest among visitors. Fifth, movie promoters will have to set a sufficient promotional period for visitors to be aware of the film in advance. Finally, movie writers will have to create scenarios with a variety of materials that meet the needs of visitors. Also, movie officials will have to develop or create a mechanism for those who watch the movie to practice oral and cognitive skills.