• The Journal of Industrial Distribution & Business
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• v.13 no.9
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• pp.37-50
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• 2022

Purpose: The purpose of this study is to explore and compare research trends in Korea and overseas academic papers on social media marketing, and to present new academic perspectives for the future direction in Korea. Research design, data and methodology: We used English abstract of research paper (Korea's: 1,349, overseas': 5,036) for word frequency analysis, topic modeling, and trend analysis for each topic. Results: The results of word frequency and co-occurrence frequency analysis showed that Korea researches focused on the experiential values of users, and overseas researches focused on platforms and content. Next, 13 topics and 12 topics for Korea and overseas researches were derived from topic modeling. And, trend analysis showed that Korean studies were different from overseas in applying marketing methods to specific industries and they were interested in the short-term performance of social media marketing. Conclusions: We found that the long-term strategies of social media marketing and academic interest in the overall industry will necessary in the future researches. Also, data mining techniques will necessary to generate more general results by quantifying various phenomena in reality. Finally, we expected that continuous and various academic approaches for volatile social media is effective to derive practical implications.

• Korean Journal of Social Welfare
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• v.42
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• pp.7-40
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• 2000

This paper examines the changes $(1982{\sim}1992)$ of social welfare expenditures of 12 welfare states. This paper focuses on two questions. First, to what extent have there been changes in social welfare expenditure (total social welfare expenditures, income support expenditures, social service expenditures) of 12 welfare states? Second, what are the causes of the changes in social welfare expenditures? Using Comparative Welfare States Data Set by Stephens(1997) and Social Expenditure Database by OECD (1999), this paper attempts to answer two questions. Fuller-Battese model, a data analysis method in pooled cross-sectional time-series analysis, is adopted to identify variables predicting social welfare expenditure changes. This paper analyzes the predictors separately according to the types of welfare states by Esping-Andersen (1990). Predictors are different by the types of welfare states; thus, economic variables such as GDP and financial deficiency have effects on social welfare expenditures of Liberal and Corporatist welfare states. while they have no effects in Social Democratic welfare states. Political variables has effects on social welfare expenditures of Corporatist welfare states, not of Liberal and Social Democratic welfare states. Demographic variables has effects on social welfare expenditures of Social Democratic welfare states rather than Liberal and Corporatist welfare states. This paper provides an additional knowledge about social welfare expenditure changes of 12 welfare states and discusses implications for the development of welfare state in Korea.

• Journal of Information Technology Applications and Management
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• v.25 no.4
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• pp.185-196
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• 2018

This study investigates the social network among authors to improve the quality of Panel researches. Korea Health Panel (KHP), implemented by the collaborative work between KIHASA (Korea Institute for Health and Social Affairs) and NHIC (National Health Insurance Service) since 2008, provides a critical infrastructure for policy making and management for insurance system and healthcare service. Using bibliographic data extracted from academic databases, eighty articles were extracted in domestic and international journals from 2008 to 2014, April. Data were analyzed by NetMiner 4.0, social network analysis software, to identify the extent to which authors are involved in healthcare use research and the patterns of collaboration between them. Analysis reveals that most authors publish a very small number of articles and collaborate within tightly knit circles. Centrality measures confirm these findings by revealing that only a small percentage of the authors are structurally dominant, and influence the flow of communication among others. It leads to the discovery of dependencies between the elements of the co-author network such as affiliates in health panel communities. Based on these findings, we recommend that Korea Health Panel could benefit from cultivating a wider base of influential authors and promoting broader collaborations.

• Korean Journal of Organic Agriculture
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• v.29 no.3
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• pp.317-332
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• 2021

This study estimated the predictive onion yield through Stepwise regression of big data and weather variables by onion growing season. The economic feasibility of onion observations using big data was analyzed using estimated predictive data. The social welfare effect was estimated through the model of Harberger's triangle using onion yield prediction with big data and it without big data. Predicted yield using big data showed a deviation of -9.0% to 4.2%. As a result of estimating the social welfare effect, the average annual value was 23.3 billion won. The average annual value of social welfare effects if big data was not used was measured at 22.4 billion won. Therefore, it was estimated that the difference between the social welfare effect when the prediction using big data was used and when it was not was about 950 million won. When these results are applied to items other than onion items, the effect will be greater. It is judged that it can be used as basic data to prove the justification of the agricultural observation project. However, since the simple Harberger's triangle theory has the limitation of oversimplifying reality, it is necessary to evaluate the economic value through various methods such as measuring the effect of agricultural observation under a more realistic rational expectation hypothesis in future studies.

• Journal of the Korea Safety Management & Science
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• v.14 no.4
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• pp.229-238
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• 2012

Within last 10 years, internet has become a daily activity, and humankind had to face the Data Deluge, a dramatic increase of digital data (Economist 2012). Due to exponential increase in amount of digital data, large scale data has become a big issue and hence the term 'big data' appeared. There is no official agreement in quantitative and detailed definition of the 'big data', but the meaning is expanding to its value and efficacy. Big data not only has the standardized personal information (internal) like customer information, but also has complex data of external, atypical, social, and real time data. Big data's technology has the concept that covers wide range technology, including 'data achievement, save/manage, analysis, and application'. To define the connected technology of 'big data', there are Big Table, Cassandra, Hadoop, MapReduce, Hbase, and NoSQL, and for the sub-techniques, Text Mining, Opinion Mining, Social Network Analysis, Cluster Analysis are gaining attention. The three features that 'bid data' needs to have is about creating large amounts of individual elements (high-resolution) to variety of high-frequency data. Big data has three defining features of volume, variety, and velocity, which is called the '3V'. There is increase in complexity as the 4th feature, and as all 4features are satisfied, it becomes more suitable to a 'big data'. In this study, we have looked at various reasons why companies need to impose 'big data', ways of application, and advanced cases of domestic and foreign applications. To correspond effectively to 'big data' revolution, paradigm shift in areas of data production, distribution, and consumption is needed, and insight of unfolding and preparing future business by considering the unpredictable market of technology, industry environment, and flow of social demand is desperately needed.

• Journal of Agricultural Extension & Community Development
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• v.27 no.3
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• pp.111-124
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• 2020

This study begins with an interest in community capacity, the basis for mobilizing community action and the driving force of community development. The study aims to identify the structural equation model of community capacity, social participation, satisfaction in life, and the impact relationship and to verify the differences between urban and rural areas. The analysis data used the 2018Korean Social Integration Survey, which is the statistical data for national approval. The analysis method was performed by using SPSS was used to perform descriptive analysis and t-test, and the structural equation model. Multi-group analysis of AMOS was also performed to verify the research model. As the result of analysis, both the condition and status of community capacity and social participation, which are products of community capacity, showed a higher average of rural areas than urban areas. As a result of the analysis of the structural equation model between community capacity, social participation, and life satisfaction, differences between rural and urban groups were identified. In rural areas, both the capacity-condition and the capacity-status variables act as positive factors for social participation and life satisfaction, but in urban areas, the path of capacity-condition, social participation, capacity-status and life satisfaction was significant. On the other hand, social participation variables acted as a factor of direct and indirect negatively influence on life satisfaction. Therefore, it can be said that the quality of community capacity in rural areas is superior to that of urban areas.

• Journal of the Korean Society of School Health
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• v.28 no.3
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• pp.248-255
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• 2015

Purpose: This study was conducted to explore the relationship between high school students' mental social health and their tendency toward social networking addiction. Methods: The subjects were 543 high school boys and girls living in D city. The data were collected from the 3rd to 21st of March in 2014. Data were analyzed using t-test, ANOVA, Duncan's post-hoc test, Pearson's correlation analysis, and hierarchical regression with SPSS/ Win 21.0. Results: Social networking addiction showed significant differences depending on gender (t=-7.03, p<.001), academic achievement (t=4.571, p=.011), and the level of maternal education (t=3.344, p=.019). Social health was correlated with the tendency toward social networking addiction. Multiple regression analysis found that gender, academic achievement and social health were associated with the level of social networking addiction (F=8.750, p<.001, Adj. $R^2=.201$). Conclusion: The results suggest that it is necessary to take into account gender characteristics, academic achievement and social health in order to develop effective management programs for social networking addiction among high school students.

• The Journal of the Korea Contents Association
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• v.20 no.5
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• pp.118-127
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• 2020

The paper introduces trends and methodological challenges of quantitative Korean text analysis by using the case studies of academic and news media articles on "migration" and "immigration" within the periods of 2017-2019. The quantitative text analysis based on natural language processing technology (NLP) and this became an essential tool for social science. It is a part of data science that converts documents into structured data and performs hypothesis discovery and verification as the data and visualize data. Furthermore, we examed the commonly applied social scientific statistical models of quantitative text analysis by using Natural Language Processing (NLP) with R programming and Quanteda.

• The Korean Journal of Applied Statistics
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• v.31 no.5
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• pp.655-665
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• 2018

Social network services (SNS) have become the most common tool for the communication of public and private opinions as well as public issues; consequently, one may form or drive public opinions to advocate by spreading positive content using SNS. Controversy for survey data based opinion poll accuracy continues in relation to response rate or sampling methodology. This study suggests complementary measures that additionally consider the sentiment analysis results of unstructured data on a social network by data crawling and sentiment dictionary adjustment process. The suggested method shows the improvement of prediction accuracy by decreasing error rates.

• Journal of Distribution Science
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• v.12 no.7
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• pp.23-35
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• 2014

Purpose - This study aims to explore the effects of social responsibility activities and business ethics practices on corporate trust and loyalty in the context of a large retail distribution business. Research design, data, and methodology - The data collected was analyzed using PASW Statistics 18.0. In order to verify the demographic characteristics, frequency analysis was conducted on the data. Results - The results of the study were as follows. First, social responsibility activities had a significant effect on corporate trust. Second, both corporate social responsibility activities and business ethics practices had significant effects on loyalty. Third, corporate trust had a significant effect on loyalty. Fourth, corporate social responsibility activities and consumer protection activities had a partial mediation effect, while environmental protection activities and social contribution activities had complete mediation effects. Conclusions - This study clarified and explained the factors of corporate social responsibility activities and business ethics practices that customers value, and analyzed the influence of these factors on corporate trust and loyalty.