• Journal of Korean Dental Hygiene Science
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• v.5 no.2
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• pp.97-104
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• 2022

Background: Due to the declining number of students preparing for university entrance exams , the quota of universities has been decreasing continuously. This situation became increasingly diverse as new media used online, mobile, and PR tools to continuously invite students. This study is aimed at offering the helpful data to plan an effective PR strategy by analyzing the correlation between the major selection and satisfaction of the department's social media usage among freshmen majoring in dental hygiene. Methods: The collected data from the self-reported survey with freshmen were analyzed using the SPSS 22.0 program. The survey items were motive to select the major, social media platform that subjects used, reasons to use the media, time to visit the department's social media platform, and satisfaction level on the department's social media platform, using a 5-point Likert Scale. Results: The reasons for choosing a major were given by 32.2% and 15.9% respondents, respectively, as the vision after graduation and practice facilities. 39.9% and 31.4% used Instagram and YouTube for social media platforms, respectively, for using social media platform; 26.9% and 26.3% visited the department's social media before and after entering the university, respectively; 46.4% and 24.9% used Instagram and YouTube for department social media; and they generally satisfied with the contents of the department's social media. 40.9% of them said that information from the department's social media was useful. 33.8% of them said the information from the department's social media exceeded their expectations. 46.8% of them answered that the department's social media made the department's image positive. 33.4% got interested in the major more due to the department's social media. According to 32.1% of respondents, the department's social media was helpful in deciding on a major. With 35.4%, a positive correlation was discovered between the department's practice facilities and satisfaction on the department's social media. Conclusion: It is thought that the department's social media should try continuously by uploading the contents to meet the users' needs on a regular basis and seeking the plans to be able to collect various opinions using surveys through the related social media so that students can select the major and, moreover, lead the positive direction to adapt the university life under the unfamiliar environment after admission.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.149-169
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• 2018

Korea is currently accumulating a large amount of data in public institutions based on the public data open policy and the "Government 3.0". Especially, a lot of data is accumulated in the tourism field. However, the academic discussions utilizing the tourism data are still limited. Moreover, the openness of the data of restaurants, hotels, and online tourism information, and how to use SNS Big Data in tourism are still limited. Therefore, utilization through tourism big data analysis is still low. In this paper, we tried to analyze influencing factors on foreign tourists' satisfaction in Korea through numerical data using data mining technique and R programming technique. In this study, we tried to find ways to revitalize the tourism industry by analyzing about 36,000 big data of the "Survey on the actual situation of foreign tourists from 2013 to 2015" surveyed by the Korea Culture & Tourism Research Institute. To do this, we analyzed the factors that have high influence on the 'Satisfaction', 'Revisit intention', and 'Recommendation' variables of foreign tourists. Furthermore, we analyzed the practical influences of the variables that are mentioned above. As a procedure of this study, we first integrated survey data of foreign tourists conducted by Korea Culture & Tourism Research Institute, which is stored in the tourist information system from 2013 to 2015, and eliminate unnecessary variables that are inconsistent with the research purpose among the integrated data. Some variables were modified to improve the accuracy of the analysis. And we analyzed the factors affecting the dependent variables by using data-mining methods: decision tree(C5.0, CART, CHAID, QUEST), artificial neural network, and logistic regression analysis of SPSS IBM Modeler 16.0. The seven variables that have the greatest effect on each dependent variable were derived. As a result of data analysis, it was found that seven major variables influencing 'overall satisfaction' were sightseeing spot attraction, food satisfaction, accommodation satisfaction, traffic satisfaction, guide service satisfaction, number of visiting places, and country. Variables that had a great influence appeared food satisfaction and sightseeing spot attraction. The seven variables that had the greatest influence on 'revisit intention' were the country, travel motivation, activity, food satisfaction, best activity, guide service satisfaction and sightseeing spot attraction. The most influential variables were food satisfaction and travel motivation for Korean style. Lastly, the seven variables that have the greatest influence on the 'recommendation intention' were the country, sightseeing spot attraction, number of visiting places, food satisfaction, activity, tour guide service satisfaction and cost. And then the variables that had the greatest influence were the country, sightseeing spot attraction, and food satisfaction. In addition, in order to grasp the influence of each independent variables more deeply, we used R programming to identify the influence of independent variables. As a result, it was found that the food satisfaction and sightseeing spot attraction were higher than other variables in overall satisfaction and had a greater effect than other influential variables. Revisit intention had a higher ${\beta}$ value in the travel motive as the purpose of Korean Wave than other variables. It will be necessary to have a policy that will lead to a substantial revisit of tourists by enhancing tourist attractions for the purpose of Korean Wave. Lastly, the recommendation had the same result of satisfaction as the sightseeing spot attraction and food satisfaction have higher ${\beta}$ value than other variables. From this analysis, we found that 'food satisfaction' and 'sightseeing spot attraction' variables were the common factors to influence three dependent variables that are mentioned above('Overall satisfaction', 'Revisit intention' and 'Recommendation'), and that those factors affected the satisfaction of travel in Korea significantly. The purpose of this study is to examine how to activate foreign tourists in Korea through big data analysis. It is expected to be used as basic data for analyzing tourism data and establishing effective tourism policy. It is expected to be used as a material to establish an activation plan that can contribute to tourism development in Korea in the future.