• Journal of Broadcast Engineering
• /
• v.23 no.4
• /
• pp.536-548
• /
• 2018

Public data has been transformed from provider-oriented information disclosure to a form of personalized information sharing centered on individual citizens since government 3.0. As a result, the government is implementing policies and projects to maximize the value of public data and increase reuse. This study analyzes the issues related to public data in the news and seeks the status of government agencies and government projects by issue. We conducted semantic analysis on domestic online news and public agency bidding information including public data and conducted the work of linking major key words derived with social and economic values inherent in public data. As a result, major issues related to public data were divided into broader access to public data, growth of new technology, cooperation and conflict among stakeholders, and utilization of the private sector, which were closely related to transparency, efficiency, participation, and innovation mechanisms. Also major agencies of four issues include the Ministry of Strategy and Finance and Seoul, Ministry of Culture, Sports and Tourism and Gyeonggi-do, Ministry of Trade, Industry and Energy and Incheon, and Ministry of Land, Infrastructure and Transport and Gyeongsangbuk-do. Most of the issues are being led by the government.

• Journal of Korea Technology Innovation Society
• /
• v.13 no.1
• /
• pp.1-27
• /
• 2010

In this paper We analyze the correlation between investment and performance of Korean R&D programs, by six factors diversified, based on evolutionary economics of technology. National Science and Technology Information Service(NTIS) started from March, 2008 was used for collecting investment and performance data of national R&D program. We search the investment cost according to science-technology standard classification of Korea, research conductors, socio-economic objectives and cooperation types per year from 2002 to 2008, and we regard this data as "investment". Similarly, we search the number of papers, patents, commercializations, royalties and so forth according to science technology standard classification of Korea, research organizations, socio-economic objectives and cooperation types per year from 2002 to 2008, and this data is regarded as "performance". We expected analysis results of this investment and performance data confirm the diversified factors to affect advancement of science and technology. And we though, as a result, we will get some meaningful directions of investment of national R&D from the analysis results. But this study has several limitations because we did not consider enough microscopic characteristics of sector or technology, research organizations, cooperation network types, and external effect of social, politic, cultural factors.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.18 no.11
• /
• pp.239-251
• /
• 2017

This study attempted to identify the health behaviors and related factors of lifestyle related diseases among some public officials. The study subjects were 729 administrative officers of the general public office of the government in D metropolitan city. The data collection was conducted by self-administered questionnaire from February 1 to March 31, 2016. As a result, the health behavior score for lifestyle related diseases showed a significant positive correlation with vulnerability, the effectiveness of health behavior and information obtained from the media about lifestyle-related diseases, while it showed a significant negative correlation with the barriers to health behaviors concerning lifestyle related diseases. As a result of the covariance structure analysis, vulnerability and seriousness about lifestyle related diseases were the most important factors affecting health behavior for lifestyle related diseases. The next most important factors were a family history of lifestyle related diseases, information obtained from the media, effectiveness of and barriers to health behavior, instrumental support, and emotional support. These results suggest that each factor constituting the Health Belief Model (HBM) (perceived vulnerability and seriousness about lifestyle related diseases, perceived effectiveness and barriers to health behaviors, family history of lifestyle related diseases, information obtained from the mass media about lifestyle related diseases, social support network for lifestyle related diseases) is an important factor to consider in practicing health behaviors for lifestyle related diseases. Therefore, it is important to accurately understand the factors related to the practice of the health behaviors of the subjects and to manage them continuously.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.17 no.1
• /
• pp.281-290
• /
• 2017

This study aims to determine how demographic characteristics and SNS use traits of audiences are different depending on preferred performance types such as pop music concert, musical; play, dancing and ballet. SNS use traits are as follows: duration of SNS use, average number of access to SNS account, average time of SNS use, SNS activity type, motivation for SNS use, preferable type of SNS, annual total number of performance watched, and method to gain performance information. Also, the study was conducted to get significant insights in designing marketing strategy using social network services. The results are as follows. First, the result of examining audience's demographic factors depending on preferred performance type showed meaningful differences in sex, age, marital status, form of family, academic level, job and monthly income of the audiences. Second, SNS use traits of the audiences according to preferred performance genres vary in duration of SNS use, average number of access to SNS account, average time of SNS use, SNS activity type, motivation for SNS use, method to gain performance information. These findings showed that demographic characteristics and SNS use traits needed to be classified more specifically based on genres. Additionally, marketing strategy using performance information, traits of contents and customers' patterns through SNS should be specifically developed based on specified target.

• Journal of the Economic Geographical Society of Korea
• /
• v.23 no.1
• /
• pp.56-70
• /
• 2020

This study identifies the impact of social network service (SNS) on the spatial characteristics of retail stores locations in the hyper-connected society, which have been closely related to the everyday lives of urban residents. In particular, we focus on the changes in the spatial distribution of restaurants since the information retrieval process was added to the decision-making process of a consumer's restaurant selection. Empirically, we analyze restaurants in Seoul, Korea since the smart-phone was introduced. By applying the kernel density estimation and Moran's I index, we examine the changes in the spatial distribution pattern of restaurants during the last ten years for running, newly-open and closed restaurants as well as SNS popular ones. Finally, we develop a spatial regression model to identify geographic features affecting their locations. As the results, we identified geographical variables and online factors that influence the location of restaurants. The results of this study could provide important groundwork for food and beverage location planning and policy formulation.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.16 no.6
• /
• pp.141-155
• /
• 2017

As the use of SNS becomes more active, many people are posting their thoughts about specific events in their SNS in the form of text. As a result, SNS is used in various fields such as finance and distribution to conduct service satisfaction surveys and consumer monitoring. However, in the transportation area, there are not enough cases to utilize unstructured data analysis such as emotional analysis. In this study, we developed an emotional analysis methodology that can be used in transportation by using highway VOC data, which is atypical data collected by Korea Expressway Corporation. The developed methodology consists of morpheme analysis, emotional dictionary construction, and emotional discrimination of the collected unstructured data. The developed methodology was verified using highway related tweet data. As a result of the analysis, it can be guessed that many information and information about the construction and the accident were related to the highway during the analysis period. Also, it seems that users complain about the delay caused by construction and accident.

• Management & Information Systems Review
• /
• v.37 no.4
• /
• pp.41-62
• /
• 2018

As the volume of unstructured data increases through various social media, Internet news articles, and blogs, the importance of text analysis and the studies are increasing. Since text analysis is mostly performed on a specific domain or topic, the importance of constructing and applying a domain-specific dictionary has been increased. The quality of dictionary has a direct impact on the results of the unstructured data analysis and it is much more important since it present a perspective of analysis. In the literature, most studies on text analysis has emphasized the importance of dictionaries to acquire clean and high quality results. However, unfortunately, a rigorous verification of the effects of dictionaries has not been studied, even if it is already known as the most essential factor of text analysis. In this paper, we generate three dictionaries in various ways from 39,800 news articles and analyze and verify the effect each dictionary on the accuracy of document classification by defining the concept of Intrinsic Rate. 1) A batch construction method which is building a dictionary based on the frequency of terms in the entire documents 2) A method of extracting the terms by category and integrating the terms 3) A method of extracting the features according to each category and integrating them. We compared accuracy of three artificial neural network-based document classifiers to evaluate the quality of dictionaries. As a result of the experiment, the accuracy tend to increase when the "Intrinsic Rate" is high and we found the possibility to improve accuracy of document classification by increasing the intrinsic rate of the dictionary.

• Journal of Korea Entertainment Industry Association
• /
• v.15 no.4
• /
• pp.359-367
• /
• 2021

This study tried to examine the factors that affect the entrepreneurial intentions in the field of culture and tourism industry. Through this, it was attempted to present strategic implications for start-up plans to prospective entrepreneurs in the cultural tourism industry. As a result of the study, the following implications were drawn. First, prospective entrepreneurs in the field of culture and tourism industry need to analyze the start-up items they want to start and systematically design a start-up plan based on market research. Also, by analyzing various start-up cases, it is necessary to secure various prior experiences of failure and success. Second, prospective entrepreneurs in the field of culture and tourism industry will need to increase their interest in starting a business by completing various entrepreneurship education conducted by more diverse institutions and schools than now, and they will have to increase the sense of achievement and willpower that can appear in education. In addition, by making efforts to create human relationships through various entrepreneurship education, efforts should be made to show the utilization of human networks and information sharing when starting a business. Lastly, prospective entrepreneurs in the field of culture and tourism industry should visit startup-related institutions and receive education and advice from experts in order to acquire various information. In addition, efforts should be made to provide more diverse start-up support by obtaining information on start-ups implemented by the state.

• Journal of Korea Society of Industrial Information Systems
• /
• v.27 no.5
• /
• pp.13-24
• /
• 2022

SNS has become a very close service to our daily life. As marketing is done through SNS, places often called hot places are created, and users are flocking to these places. However, it is often crowded with a large number of people in a short period of time, resulting in a negative experience for both visitors and service providers. In order to improve this problem, it is necessary to recognize the congestion level, but the method to determine the congestion level in a specific area at an individual level is very limited. Therefore, in this study, we tried to propose a system that can identify the congestion level information and the characteristics of visitors to a specific tourist destination by using the data on the SNS. For this purpose, posting data uploaded by users and image analysis were used, and the performance of the proposed system was verified using the Naver DataLab system. As a result of comparative verification by selecting three places by type of tourist destination, the results calculated in this study and the congestion level provided by DataLab were found to be similar. In particular, this study is meaningful in that it provides a degree of congestion based on real data of users that is not dependent on a specific company or service.

• Journal of the Korean Society for Library and Information Science
• /
• v.57 no.4
• /
• pp.333-351
• /
• 2023

This study investigates user behavior in library spaces through the lens of AI camera analytics. By leveraging the face recognition and tracking capabilities of AI cameras, we accurately identified the gender and age of visitors and meticulously collected video data to track their movements. Our findings revealed that female users slightly outnumbered male users and the dominant age group was individuals in their 30s. User visits peaked between Tuesday to Friday, with the highest footfall recorded between 14:00 and 15:00 pm, while visits decreased over the weekend. Most visitors utilized one or two specific spaces, frequently consulting the information desk for inquiries, checking out/returning items, or using the rest area for relaxation. The library stacks were used approximately twice as much as they were avoided. The most frequented subject areas were Philosophy(100), Religion(200), Social Sciences(300), Science(400), Technology(500), and Literature(800), with Literature(800) and Religion(200) displaying the most intersections with other areas. By categorizing users into five clusters based on space utilization patterns, we discerned varying objectives and subject interests, providing insights for future library service enhancements. Moreover, the study underscores the need to address the associated costs and privacy concerns when considering the broader application of AI camera analytics in library settings.