The purpose of this study is to provide clues to social welfare policy making by revealing discourse on social intervention and response based on big data on elderly living alone in the COVID-19 situation. Keyword analysis, network analysis, and topic analysis were utilized to explore the ways in which news media have portrayed challenges facing older individuals and the ways in which the central and local government as well as private organization have responded to them. Results are as follows. First, networks(degree, closeness, betweenness) were formed around region, delivery, society, support, and vulnerability, suggesting an increased demand for economic assistance and social support as well as stronger service delivery systems. Second, key topics derived included "establishing public delivery systems", "establishing local networks", "Managing care gap", "Establishing a private economic support system", and "Establishing service organization system". Based on the research results, discourse on the organic role of government, communities and the private sector has been presented, suggesting policy and practical implications by proposing a discussion on how to intervene for elderly living alone in disaster situations such as COVID-19.
This study aims to explore the issue of drones and crime in newspaper articles. BIG KINDS, an online news archive of the Korea Press Foundation, collected 1,213 newspaper articles that met the terms of "drone" and "crime" in 11 central and 28 regional comprehensive newspapers between January 1, 1990 and May 1, 2021. Among them, we perform keyword frequency, centrality analysis, network structure construction, CONCOR analysis, and density matrix analysis on 117 key keywords. According to the analysis, the main issues were classified into eight, and the report analysis on drones and crimes in newspaper articles showed that the government's policy-making and social problems on protecting people's privacy, preventing illegal filming, securing navigation safety, social security and resolution. This study attempts to expand the field of humanities and social studies related to drones and crime, and specifically suggests the current status and counterplan against drone-related crimes as policy implications and media implications.
As data broadcasting has become available, diverse contents can now be provided through digital TV, IPTV and DMB; yet it is true in the current situation that killer contents are insufficient that can satisfy users. On the contrary, in case of the web, with the advent of web 2.0 aiming at user-centered services, the contents market has grown greatly. The ideas and technologies of Web 2.0, if gratified into data broadcasting, are expected to make a contribution to the vitalization of contents. This paper proposes a method of using RSS, as a concrete example of applying web 2.0 to data broadcasting. Accordingly, we have developed a system for producing data services for the ground wave DMB data broadcasting, by using RSS at the stage of authoring news and the like, for which provision of the latest information is important. And for IPTV, we have developed a data broadcasting application so that users can select the RSS they want, as well as a creation system for using RSS at the authoring stage. It is anticipated that the application of RSS by means of the system will simplify the authoring process, making easy the provision of the latest information through the web, and thereby making possible the provision of diverse services to users.
Purpose - According to agency theory, managers have incentives to adjust firm revenues to meet earnings expectations or delay bad news disclosure because of performance-based compensation and their reputation in the market. When the bad news accumulates, stock prices fail to reflect all available information. Thus, market prices of stocks are higher than their intrinsic value. After all, bad news crosses the tipping point, it comes out all at once. That results in stock crashes. Auditors can decrease stock crash risk by reducing agency costs through their informational role. Especially, stock price crash risk is expected to be lower for firms adopting high-quality audits. We focus on distribution and service industry to examine the relation between audit quality and stock price crash risk. Industry specialization and auditor size are used as proxies for auditor quality. Research design, data and methodology - Our sample contains distribution and service industry firms listed in KOSPI and KOSDAQ during a period of 2004-2011. We use a logistic regression to test whether auditor quality influences crash risk. Auditor quality was measured by industry specialist auditor and Big4 / non-Big4 dichotomy. Following the approach in prior researches, we use firm-specific weekly returns to measure crash risk. Firms experiencing at least one stock price crash in a specific week during year are classified as the high risk group. Results - The result of analyzing 429 companies in distribution and service industry is summarized as follows: Above all, it is shown that higher audit quality has a significant negative(-) effect on the crash risk. Crash risk is alleviated for firms audited by industry specialist auditors and Big 4 audit firms. Therefore, our results show that hypotheses are supported. Conclusions - This study is very meaningful as the first study which investigated the effects of high audit quality on stock price crash risk. We provide evidence that high-quality auditors reduce stock price crash risk. Our finding implies that the risk of extreme losses can be reduced through screening of high-quality auditors. Therefore investors and regulators may utilize our findings in their investment and rule making decisions.
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
/
v.32
no.6
/
pp.651-659
/
2014
With the popularization of big data environment, big data have been highlighted as a key information strategy to establish national spatial data infrastructure for a scientific land policy and the extension of the creative economy. Especially interesting from our point of view is the cadastral information is a core national information source that forms the basis of spatial information that leads to people's daily life including the production and consumption of information related to real estate. The purpose of our paper is to suggest the scheme of big data analytics with respect to the articles of cadastral resurvey project in order to approach cadastral information in terms of spatial data integration. As specific research method, the TM (Text Mining) package from R was used to read various formats of news reports as texts, and nouns were extracted by using the KoNLP package. That is, we searched the main keywords regarding cadastral resurvey, performing extraction of compound noun and data mining analysis. And visualization of the results was presented. In addition, new reports related to cadastral resurvey between 2012 and 2014 were searched in newspapers, and nouns were extracted from the searched data for the data mining analysis of cadastral information. Furthermore, the approval rating, reliability, and improvement of rules were presented through correlation analyses among the extracted compound nouns. As a result of the correlation analysis among the most frequently used ones of the extracted nouns, five groups of data consisting of 133 keywords were generated. The most frequently appeared words were "cadastral resurvey," "civil complaint," "dispute," "cadastral survey," "lawsuit," "settlement," "mediation," "discrepant land," and "parcel." In Conclusions, the cadastral resurvey performed in some local governments has been proceeding smoothly as positive results. On the other hands, disputes from owner of land have been provoking a stream of complaints from parcel surveying for the cadastral resurvey. Through such keyword analysis, various public opinion and the types of civil complaints related to the cadastral resurvey project can be identified to prevent them through pre-emptive responses for direct call centre on the cadastral surveying, Electronic civil service and customer counseling, and high quality services about cadastral information can be provided. This study, therefore, provides a stepping stones for developing an account of big data analytics which is able to comprehensively examine and visualize a variety of news report and opinions in cadastral resurvey project promotion. Henceforth, this will contribute to establish the foundation for a framework of the information utilization, enabling scientific decision making with speediness and correctness.
Objectives : Previous research on texts specializing in acupuncture and moxibustion in Korea have mostly been focused on those written in the Joseon period, leaving an academic void in the modern and contemporary eras. This research on the "Yeongsochimgugyeong" was undertaken to help readers' understanding of the text and to provide basic material for further research on modern-contemporary education of acupuncture and moxibustion. Methods : The original text of "Yeongsochimgugyeong" was examined along with books and news articles on related people. Information that was difficult to obtain through written documents was supplemented by interviews with people who knew about the situation at the time. The findings were organized as 1) the author and related people and 2) introduction of "Yeongsochimgugyeong". Results and Conclusions : The original text of "Yeongsochimgugyeong" was written by teacher Jeon, Gwangok, interpreted and annotated by his disciple Gwon, Yeongjun. It is presumed that they wrote this book as educators of Korean medicine for educational purposes on acupuncture and moxibustion before and after the Japanese colonial era. The book is consisted of an overview of meridianology, details on points and meridians, supplementing and draining methods, similar to the current text book. The contents and expressions of "Yeongsochimgugyeong" reflect the state of acupuncture and moxibustion education of the early and mid $20^{th}$ century, making it a valuable resource.
While much in the field of public management has emphasized the importance of nonprofit advocacy activities in policy and decision-making procedures, few have considered the relevance and impact of leading actors on structuring diverse patterns of information sharing and communication through social media. Building nonprofit advocacy is a complicated process for a single organization to undertake, but social media applications such as Facebook and Twitter have facilitated nonprofit organizations and stakeholders to effectively share information and communicate with each other for identifying their mission as it relates to environmental issues. By analyzing the Australian Marine Conservation Society's (AMCS) Twitter network data from the period 1 April to 20 April, 2013, this research discovered diverse patterns in nonprofit advocacy by leading actors in building advocacy. Based on the webometrics approach, analysis results show that nonprofit advocacy through social media is structured by dynamic information flows and intercommunications among participants and followers of the AMCS. Also, the findings indicate that the news media and international and domestic nonprofit organizations have a leading role in building nonprofit advocacy by clustering with their followers.
The purpose of this study was to examine how recently fashion corporate did use SNS applications for their product promotion strategies as case studies, and to provide what kinds of SNS marketing strategies would be developed for fashion corporate. Specifically, this study was focused on Twitter among SNS applications. For this study, Internet webs, news paper, articles, and other press work were used for resources. Five fashion corporate such as Buckaroo, MLB, North Faces, Kolon, and ABC Mart were analyzed. As the results, first, fashion corporate used Twitter as the marketing tool for their product promotion. Second, they tried to make an increase the numbers of Twitter follower from their customers. Third, Twitter was used for making higher customer loyalty by fashion corporate through a variety of program such as special events, game, music, or viral marketing. However, there were still some limitations on fashion corporate's Twitter usage, compared to other non-fashion corporate. Thus, fashion corporate needs to provide more creative and unique Twitter marketing strategies. Therefore, based on these results, fashion brand merchandising marketing strategies of fashion products would be provided from this study.
Recently, the volume of unstructured text data generated by various social media has been increasing rapidly; consequently, the use of text mining to support decision-making has also been growing. In particular, academia and industry are paying significant attention to topic analysis in order to discover the main issues from a large volume of text documents. Topic analysis can be regarded as static analysis because it analyzes a snapshot of the distribution of various issues. In contrast, some recent studies have attempted to perform dynamic issue tracking, which analyzes and traces issue trends during a predefined period. However, most traditional issue tracking methods have a common limitation : when a new period is included, topic analysis must be repeated for all the documents of the entire period, rather than being conducted only on the new documents of the added period. Additionally, traditional issue tracking methods do not concentrate on the transition of individuals' interests from certain issues to others, although the methods can illustrate macro-level issue trends. In this paper, we propose an individual interests tracking methodology to overcome the two limitations of traditional issue tracking methods. Our main goal is not to track macro-level issue trends but to analyze trends of individual interests flow. Further, our methodology has extensible characteristics because it analyzes only newly added documents when the period of analysis is extended. In this paper, we also analyze the results of applying our methodology to news articles and their access logs.
Recently, many South Korean firms have suffered financial losses and damaged corporate images from the data breaches. Accordingly, a firm should manage their IT assets securely through an information security investment. However, the difficulty of measuring the return on an information security investment is one of the critical obstacles for firms in making such investment decisions. There have been a number of studies on the effect of IT investment so far, but there are few researches on information security investment. In this paper, based on a sample of 76 investment announcements of firms whose stocks are publicly traded in the South Korea's stock market between 2001 and 2017, we examines the market reaction to information security investment by using event study methodology. The results of the main effects indicate that self-developed is significantly related to cumulative average abnormal returns (CAARs), while no significant effect was observed for discloser, investment characteristics and firm characteristics. In addition, we find that the market reacts more favorably to the news announced by the subject of investment than the vendor, in case of investments with commercial exploitation. One of main contributions in our study is that it has revealed the factors affecting the market reaction to announcement of information security investment. It is also expected that, in practice, corporate executives will be able to help make an information security investment decision.
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