• Title/Summary/Keyword: social media activity analysis

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A Study on the UIC(University & Industry Collaboration) Model for Global New Business (글로벌 사업 진출을 위한 산학협력 협업촉진모델: 경남 G대학 GTEP 사업 실험사례연구)

  • Baek, Jong-ok;Park, Sang-hyeok;Seol, Byung-moon
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.10 no.6
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    • pp.69-80
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    • 2015
  • This can be promoted collaboration environment for the system and the system is very important for competitiveness, it is equipped. If so, could work in collaboration with members of the organization to promote collaboration what factors? Organizational collaboration and cooperation of many people working, or worth pursuing common goals by sharing information and processes to improve labor productivity, defined as collaboration. Factors that promote collaboration are shared visions, the organization's principles and rules that reflect the visions, on-line system developments, and communication methods. First, it embodies the vision shared by the more sympathetic members are active and voluntary participation in the activities of the organization can be achieved. Second, the members are aware of all the rules and principles of a united whole is accepted and leads to good performance. In addition, the ability to share sensitive business activities for self-development and also lead to work to make this a regular activity to create a team that can collaborate to help the environment and the atmosphere. Third, a systematic construction of the online collaboration system is made efficient and rapid task. According to Student team and A corporation we knew that Cloud services and social media, low-cost, high-efficiency services could achieve. The introduction of the latest information technology changes, the members of the organization's systems and active participation can take advantage of continuing education must be made. Fourth, the company to inform people both inside and outside of the organization to communicate actively to change the image of the company activities, the creation of corporate performance is very important to figure. Reflects the latest trend to actively use social media to communicate the effort is needed. For development of systematic collaboration promoting model steps to meet the organizational role. First, the Chief Executive Officer to make a firm and clear vision of the organization members to propagate the faith, empathy gives a sense of belonging should be able to have. Second, middle managers, CEO's vision is to systematically propagate the organizers rules and principles to establish a system would create. Third, general operatives internalize the vision of the company stating that the role of outside companies must adhere. The purpose of this study was well done in collaboration organizations promoting factors for strategic alignment model based on the golden circle and collaboration to understand and reflect the latest trends in information technology tools to take advantage of smart work and business know how student teams through case analysis will derive the success factors. This is the foundation for future empirical studies are expected to be present.

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Art Therapy and Hospice & Palliative Care in Korea (한국의 예술치료와 호스피스 완화의료)

  • Kim, Chang Gon
    • Journal of Hospice and Palliative Care
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    • v.18 no.2
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    • pp.85-96
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    • 2015
  • In Korea, modern art therapy was developed in the 1960s and 1970s in the form of supplementary activities for patients in psychiatry. Along with the foundation of the Korean Association for Clinical Art in 1982 by psychiatric doctors, the therapy involved more various arts forms such as music, art, dance, poetry therapy, and psychodrama. More organizations with specific expertise opened such as the Korean Art Therapy Association, Korean Art Therapy Association, etc. in the 1990s and the Korea Arts Therapy Institute in 2001. As of April 2015, the members of the Korean Art Therapy Association total 15,000, including 6,200 regular members. The arts in integrative arts therapy (IAT) is an individual's creative activity which is related to his inner world, and the forms of IAT include music, drawing, dance and poetry therapy. From the aspect of phenomenology, IAT is psychophysical therapy involving the arts that helps patients recognize and perceive their experiences with an aim of at a recovery of the body and creativity from the phenomenological aspect. It is also a therapeutic activity that targets growth and development of the body and mind. Meta-analysis of the effects of art therapy with a focus on that involving music, drawing, dance movement and IAT in recent years in Korea, significant effects were observed in all factors but physical function. The biggest effect was mentality adaptation followed by activity adaptation and physiology. In the run up to the implementation of the daily flat-rate system for the health insurance reimbursement for palliative care in July 2015, the Ministry of Health and Welfare is reviewing the coverage of music therapy, drawing therapy and flower therapy, which are currently practiced by 56 hospice institutes in Korea. This is a meaningful step because the coverage of hospice and palliative care came after that of art therapy for psychiatric patients was approved in 1977. Still, there is a need clarify the therapeutic mechanism by exploring causality among the treatment media, mediation type and treatment effects. To address the issue of indiscriminately issued licenses, more efforts are needed to ensure expertise and identity of the licensed therapists through education, training and supervision.

SNS Utilization Profiled as Per Six Continental Areas, Dance Genre, Types at Overseas Dance Arts Companies (해외무용예술단체의 6대륙 지역별, 무용장르별, 유형별, SNS 활용 프로파일)

  • Jeon, Soon-Hee;Yang, Yu-Na
    • The Journal of the Korea Contents Association
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    • v.14 no.8
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    • pp.74-83
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    • 2014
  • This study was conducted for the overall analysis for the interests, generally and uses of SNS (Social Network Service) of the overseas dance arts company. The subjects of this study were total 3,614 of countries, public, private and personal dance arts company in 100 countries on six continents. The selected 627 company which operate at least one SNS, and included them in this study. Then analyzed the SNS utilization six continental areas as per dance gener, types, and dance gener analyzed as per types. Also analyzed the SNS utilization six continental areas, dance gener as per types and obtained the following result First, It appeared that Ballet company of North America continent took advantage of SNS the most. Second, It appeared that Facebook, Twitter of North America was the most frequently used. Third, It appeared that Facebook wsa the most frequently used by traditional dance company. Fourth. Facebook, Twitter, Youtube were the most activity used by Ballet company of North America continent. In conclusion, this study recommends the policy alternatives related to the awareness of digital media, the establishment of the SNS marketing information system.

Literature Review on Applying Digital Therapeutic Art Therapy for Adolescent Substance Addiction Treatment (청소년 마약류 중독 치료를 위한 디지털치료제 예술치료 적용을 위한 문헌연구)

  • Jiwon Kim;Daniel H. Byun
    • Trans-
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    • v.16
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    • pp.1-31
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    • 2024
  • The advent of digital media has facilitated easy access for adolescents to environments conducive to the purchase of narcotics. In particular, there's an increasing trend in the purchase and consumption of narcotics mediated through Social Network Services (SNS) and messenger services. Adolescents, sensitive to such environments, are at risk of experiencing neurological and mental health issues due to narcotic addiction, increasing their exposure to criminal activities, hence necessitating national-level management and support. Consequently, the quest for sustainable treatment methods for adolescents exposed to narcotics emerges as a critical challenge. In the context of high relapse rates in narcotic addiction, the necessity for cost-effective and user-friendly treatment programs is emphasized. This study conducts a literature review aimed at utilizing digital platforms to create an environment where adolescents can voluntarily participate, focusing on the development of therapeutic content through art. Specifically, it reviews societal perceptions and treatment statuses of adolescent drug addiction, analyzes the impact of narcotic addiction on adolescent brain activity and cognitive function degradation, and explores approaches for developing digital therapeutics to promote the rehabilitation of the addicted brain through analysis of precedential case studies. Moreover, the study investigates the benefits that the integration of digital therapeutic approaches and art therapy can provide in the treatment process and proposes the possibility of enhancing therapeutic effects through various treatment programs such as drama therapy, music therapy, and art therapy. The application of art therapy methods is anticipated to offer positive effects in terms of tool expansion, diversification of expression, data acquisition, and motivation. Through such approaches, an enhancement in the effectiveness of treatments for adolescent narcotic addiction is anticipated. Overall, this study undertakes foundational research for the development of digital therapeutics and related applications, offering economically viable and sustainable treatment options in consideration of the societal context of adolescent narcotic addiction.

Color Marketing Strategy of Milk Packaging (우유 Packaging 색채 마케팅전략)

  • Kim, Kyung-Hwa;Na, Ji-Young
    • The Journal of the Korea Contents Association
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    • v.12 no.1
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    • pp.197-210
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    • 2012
  • In this research, we executed a questionnaire survey targeting men and women in 20' or more who reside in the metropolitan area and have experienced purchasing the vehicles in order to study how Promotion Mix Activity affects Brand assets, and ultimately what kind of relation it has with Purchase intention. In the statistical process of collected data, we analyzed the data by using SPSS 12.0 for Windows statistical package and AMOS 7.0 program. As the result of analysis, first, when we analyzed the relation of the Promotion Mix Activity and Brand Assets of the companies, the more affirmative the assessment on the advertising activities of the companies was, the higher the brand popularity, royalty and image increased, And it appeared that as the assessment on PR activities of the companies got more affirmative, the brand popularity, image and royalty increased. Second, as the result of the analysis of the relation between salespersons' Promotion Activities and Brand assets, it appeared that salespersons' social capacity improved Brand awareness and royalty and their strategic capacity improved Brand awareness, royalty and image. Third, seeing the result of the analysis on the relation between Brand assets and Purchase intention, it was shown that Brand popularity had a meaningful positive(+) effect upon satisfaction and repurchase(oral) intention, and Brand royalty had a meaningful positive(+) effect upon satisfaction and repurchase(oral) intention. In addition, it appeared that Brand image had a meaningful positive(+) effect upon satisfaction and repurchase(oral) intention, and finally it could be known that Brand assets had a close correlation with Purchase intention. Therefore, this research established the color marketing strategy as follows. First, we shall build up the functional role such as aesthetic favor, information communication, protection of ecosystem, publicity reinforcement etc. so as to emphasize the properties of the package design; second, we have to construct the color marketing strategy to convey the images of the commodity besides the psychological and physiological utility which colors grants, the utility used in visual conveyance as communication media; third, we should build the color marketing strategy for the integration of company image; finally we have to compose the colors fitted for the company and product style and introduce design marketing using company colors.

Construction of Consumer Confidence index based on Sentiment analysis using News articles (뉴스기사를 이용한 소비자의 경기심리지수 생성)

  • Song, Minchae;Shin, Kyung-shik
    • Journal of Intelligence and Information Systems
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    • v.23 no.3
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    • pp.1-27
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    • 2017
  • It is known that the economic sentiment index and macroeconomic indicators are closely related because economic agent's judgment and forecast of the business conditions affect economic fluctuations. For this reason, consumer sentiment or confidence provides steady fodder for business and is treated as an important piece of economic information. In Korea, private consumption accounts and consumer sentiment index highly relevant for both, which is a very important economic indicator for evaluating and forecasting the domestic economic situation. However, despite offering relevant insights into private consumption and GDP, the traditional approach to measuring the consumer confidence based on the survey has several limits. One possible weakness is that it takes considerable time to research, collect, and aggregate the data. If certain urgent issues arise, timely information will not be announced until the end of each month. In addition, the survey only contains information derived from questionnaire items, which means it can be difficult to catch up to the direct effects of newly arising issues. The survey also faces potential declines in response rates and erroneous responses. Therefore, it is necessary to find a way to complement it. For this purpose, we construct and assess an index designed to measure consumer economic sentiment index using sentiment analysis. Unlike the survey-based measures, our index relies on textual analysis to extract sentiment from economic and financial news articles. In particular, text data such as news articles and SNS are timely and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. There exist two main approaches to the automatic extraction of sentiment from a text, we apply the lexicon-based approach, using sentiment lexicon dictionaries of words annotated with the semantic orientations. In creating the sentiment lexicon dictionaries, we enter the semantic orientation of individual words manually, though we do not attempt a full linguistic analysis (one that involves analysis of word senses or argument structure); this is the limitation of our research and further work in that direction remains possible. In this study, we generate a time series index of economic sentiment in the news. The construction of the index consists of three broad steps: (1) Collecting a large corpus of economic news articles on the web, (2) Applying lexicon-based methods for sentiment analysis of each article to score the article in terms of sentiment orientation (positive, negative and neutral), and (3) Constructing an economic sentiment index of consumers by aggregating monthly time series for each sentiment word. In line with existing scholarly assessments of the relationship between the consumer confidence index and macroeconomic indicators, any new index should be assessed for its usefulness. We examine the new index's usefulness by comparing other economic indicators to the CSI. To check the usefulness of the newly index based on sentiment analysis, trend and cross - correlation analysis are carried out to analyze the relations and lagged structure. Finally, we analyze the forecasting power using the one step ahead of out of sample prediction. As a result, the news sentiment index correlates strongly with related contemporaneous key indicators in almost all experiments. We also find that news sentiment shocks predict future economic activity in most cases. In almost all experiments, the news sentiment index strongly correlates with related contemporaneous key indicators. Furthermore, in most cases, news sentiment shocks predict future economic activity; in head-to-head comparisons, the news sentiment measures outperform survey-based sentiment index as CSI. Policy makers want to understand consumer or public opinions about existing or proposed policies. Such opinions enable relevant government decision-makers to respond quickly to monitor various web media, SNS, or news articles. Textual data, such as news articles and social networks (Twitter, Facebook and blogs) are generated at high-speeds and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. Although research using unstructured data in economic analysis is in its early stages, but the utilization of data is expected to greatly increase once its usefulness is confirmed.

Influence of Motivational, Social, and Environmental Factors on the Learning of Hackers (동기적, 사회적, 그리고 환경적 요인이 해커의 기술 습득에 미치는 영향)

  • Jang, Jaeyoung;Kim, Beomsoo
    • Information Systems Review
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    • v.18 no.1
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    • pp.57-78
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    • 2016
  • Hacking has raised many critical issues in the modern world, particularly because the size and cost of the damages caused by this disruptive activity have steadily increased. Accordingly, many significant studies have been conducted by behavioral scientists to understand hackers and their practices. Nonetheless, only qualitative methods, such as interviews, meta-studies, and media studies, have been employed in such studies because of hacker sampling limitations. Existing studies have determined that intrinsic motivation was the dominant factor influencing hackers, and that their techniques were mainly acquired from online hacking communities. However, such results have yet to be causally proven. This study attempted to identify the causal factors influencing the motivational and environmental factors encouraging hackers to learn hacking skills. To this end, hacker community members using the theory of planned behavior were observed to identify the causal factors of their learning of hacking skills. We selected a group of students who were developing their hacking skills. The survey was conducted over a two-week period in May 2015 with a total of 227 students as respondents. After list-wise deletion, 215 of the responses were deemed usable (94.7 percent). In summary, the hackers were aware that hacking skills are considered socially unethical, and their attitudes toward the learning of hacking skills were affected by both intrinsic and extrinsic motivations. In addition, the characteristics of the online hacking community affected their perceived behavioral control. This study introduced new concepts in the process of conducting a causal relationship analysis on a hacker sample. Moreover, this research expanded the discussion on the causal direction of subjective norms in unethical research, and empirically confirmed that both intrinsic and extrinsic motivations affect the learning of hacking skills. This study also made a practical contribution by raising the educational and policy response issues for ethical hackers and demonstrating the necessity to intensify the punishment for hacking.

Clickstream Big Data Mining for Demographics based Digital Marketing (인구통계특성 기반 디지털 마케팅을 위한 클릭스트림 빅데이터 마이닝)

  • Park, Jiae;Cho, Yoonho
    • Journal of Intelligence and Information Systems
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    • v.22 no.3
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    • pp.143-163
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    • 2016
  • The demographics of Internet users are the most basic and important sources for target marketing or personalized advertisements on the digital marketing channels which include email, mobile, and social media. However, it gradually has become difficult to collect the demographics of Internet users because their activities are anonymous in many cases. Although the marketing department is able to get the demographics using online or offline surveys, these approaches are very expensive, long processes, and likely to include false statements. Clickstream data is the recording an Internet user leaves behind while visiting websites. As the user clicks anywhere in the webpage, the activity is logged in semi-structured website log files. Such data allows us to see what pages users visited, how long they stayed there, how often they visited, when they usually visited, which site they prefer, what keywords they used to find the site, whether they purchased any, and so forth. For such a reason, some researchers tried to guess the demographics of Internet users by using their clickstream data. They derived various independent variables likely to be correlated to the demographics. The variables include search keyword, frequency and intensity for time, day and month, variety of websites visited, text information for web pages visited, etc. The demographic attributes to predict are also diverse according to the paper, and cover gender, age, job, location, income, education, marital status, presence of children. A variety of data mining methods, such as LSA, SVM, decision tree, neural network, logistic regression, and k-nearest neighbors, were used for prediction model building. However, this research has not yet identified which data mining method is appropriate to predict each demographic variable. Moreover, it is required to review independent variables studied so far and combine them as needed, and evaluate them for building the best prediction model. The objective of this study is to choose clickstream attributes mostly likely to be correlated to the demographics from the results of previous research, and then to identify which data mining method is fitting to predict each demographic attribute. Among the demographic attributes, this paper focus on predicting gender, age, marital status, residence, and job. And from the results of previous research, 64 clickstream attributes are applied to predict the demographic attributes. The overall process of predictive model building is compose of 4 steps. In the first step, we create user profiles which include 64 clickstream attributes and 5 demographic attributes. The second step performs the dimension reduction of clickstream variables to solve the curse of dimensionality and overfitting problem. We utilize three approaches which are based on decision tree, PCA, and cluster analysis. We build alternative predictive models for each demographic variable in the third step. SVM, neural network, and logistic regression are used for modeling. The last step evaluates the alternative models in view of model accuracy and selects the best model. For the experiments, we used clickstream data which represents 5 demographics and 16,962,705 online activities for 5,000 Internet users. IBM SPSS Modeler 17.0 was used for our prediction process, and the 5-fold cross validation was conducted to enhance the reliability of our experiments. As the experimental results, we can verify that there are a specific data mining method well-suited for each demographic variable. For example, age prediction is best performed when using the decision tree based dimension reduction and neural network whereas the prediction of gender and marital status is the most accurate by applying SVM without dimension reduction. We conclude that the online behaviors of the Internet users, captured from the clickstream data analysis, could be well used to predict their demographics, thereby being utilized to the digital marketing.