• Smart Media Journal
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• v.12 no.11
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• pp.27-35
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• 2023

Fourth Industrial Revolution and COVID-19 pandemic have boosted the use of Government 24 app for public service complaints in the era of non-face-to-face interactions. there has been a growing influx of complaints and improvement demands from users of public apps. Furthermore, systematic management of public apps is deemed necessary. The aim of this study is to analyze the grievances of Government 24 app users, understand the current dissatisfaction among citizens, and propose potential improvements. Data were collected from the Google Play Store from May 2, 2013, to June 30, 2023, comprising a total of 6,344 records. Among these, 1,199 records with a rating of 1 and at least one 'thumbs-up' were used for topic modeling analysis. The analysis revealed seven topics: 'Issues with certificate issuance,' 'Website functionality and UI problems,' 'User ID-related issues,' 'Update problems,' 'Government employee app management issues,' 'Budget wastage concerns ((It's not worth even a single star) or (It's a waste of taxpayers' money)),' and 'Password-related problems.' Furthermore, the overall trend of these topics showed an increase until 2021, a slight decrease in 2022, but a resurgence in 2023, underscoring the urgency of updates and management. We hope that the results of this study will contribute to the development and management of public apps that satisfy citizens in the future.

• Korean Journal of Clinical Laboratory Science
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• v.55 no.4
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• pp.314-323
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• 2023

This study assessed the desired wage guidelines for medical technologists (MTs), mainly primary care providers and those in secondary medical institutions, in 16 cities and provinces in Korea. A survey of 1,327 MTs was conducted using a structured Google questionnaire from August 1, 2022, to September 30, 2022. The wage levels differed according to gender, age, education, career, region, and employment status. There were differences in wage levels according to gender and region with less than one year of career, and the wage gap was relatively larger for woman than man. An awareness of wage compensation appropriate for work performance, and technology value compensation were low at 2.01, 2.23, and 2.30, respectively. This study suggests that primary and secondary medical institutions should provide reasonable wages compensation for MTs' work in order to create an environment where MTs can receive stable jobs and work. Moreover, the Korean Association of Medical Technologists should establish a cooperative system so that the starting wage of MTs in primary and secondary medical institutions can receive the desired wage of 34 million won.

• Smart Media Journal
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• v.13 no.1
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• pp.36-44
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• 2024

Metaverse is attracting attention as the development of virtual environment technology and the emergence of untact culture due to the COVID-19 pandemic. In this study, by analyzing users' reviews on the "Zepeto" application, which has recently attracted attention as a metaverse service, we tried to confirm changes in the requirements for the metaverse after the COVID-19 pandemic. To this end, 109,662 reviews of "Zepeto" applications written on the Google Play Store from September 2018 to March 2023 were collected, topics were extracted using LDA topic modeling technique, and topics were analyzed using the Causal Impact technique to examine how topics changed before and after based on "March 11, 2020" when the COVID-19 pandemic was declared. As a result of the analysis, five topics were extracted: application functional problems (topic1), security problems (topic 2), complaints about cryptocurrency (Zem) in the application (topic 3), application performance (topic 4), and personal information-related problems (topic 5). Among them, it was confirmed that security problems (topic 2) were most affected by the COVID-19 pandemic.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.35-50
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• 2024

This study was attempted to determine the effect of premenstrual syndrome, menstrual pain, attitudes toward menstruation, and quality of sleep on learning immersion in female college students. The subjects of the study were 166 female college students at C University in Gyeongsangnam-do, and data collection was conducted from July 01 to August 31, 2023, using a Google questionnaire. The collected data were analyzed by correlation, multiple regression analysis. Premenstrual syndrome had a significant positive correlation with attitudes toward menstruation(r=.40, p<.001) and menstrual pain(r=.33, p<.001). And sleep quality had a significant positive correlation with menstrual pain(r=.31, p<.001) and learning immersion(r=.24, p=.002). Variables that have a significant impact on learning immersion include 'irregularity in eating' (β =.20, p=.007), 'abdominal massage' to relieve menstrual pain (β=.27, p=.003), and sleep quality (β=.16, p=.038). 'Abdominal massage' to relieve menstrual pain was found to be the best predictor of learning immersion, followed by 'irregularity in eating' and sleep quality. The total explanatory power was 13.9%. Based on the above results, in order to increase learning commitment through mitigation of premenstrual syndrome, education is necessary to seek active countermeasures by increasing various treatments and interest in them, and to have a positive attitude toward menstruation by having proper eating habits.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.97-109
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• 2024

In the field of domestic tourism, tourism trend analysis of tourism consumers, both international tourists and domestic tourists, is essential not only for the Korean tourism market but also for local and governmental tourism policy makers. e will explore the keywords and sentiment analysis on social media to establish a marketing strategy plan and revitalize the domestic tourism industry through communication and information from tourism consumers. This study utilized TEXTOM 6.0 to analyze recent trends in Korean tourism. Data was collected from September 31, 2022, to August 31, 2023, using 'Korean tourism' and 'domestic tourism' as keywords, targeting blogs, cafes, and news provided by Naver, Daum, and Google. Through text mining, 100 key words and TF-IDF were extracted in order of frequency, and then CONCOR analysis and sentiment analysis were conducted. For Korean tourism keywords, words related to tourist destinations, travel companions and behaviors, tourism motivations and experiences, accommodation types, tourist information, and emotional connections ranked high. The results of the CONCOR analysis were categorized into five clusters related to tourist destinations, tourist information, tourist activities/experiences, tourism motivation/content, and inbound related. Finally, the sentiment analysis showed a high level of positive documents and vocabulary. This study analyzes the rapidly changing trends of Korean tourism through text mining on Korean tourism and is expected to provide meaningful data to promote domestic tourism not only for Koreans but also for foreigners visiting Korea.

• Clinical Endoscopy
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• v.57 no.2
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• pp.181-190
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• 2024

Background/Aims: Radiofrequency ablation (RFA) is the first-line therapy for dysplastic Barrett's esophagus (BE). Therefore, cryotherapy has emerged as an alternative treatment option. This study aimed to compare the efficacies of these two techniques based on the rates of complete eradication of intestinal metaplasia (CE-IM) and dysplasia (CE-D). Adverse events and recurrence have also been reported. Methods: An electronic search was conducted using the Medline (PubMed), Embase, LILACS, and Google Scholar databases until December 2022. Studies were included comparing cryotherapy and RFA for treating dysplastic BE with or without early esophageal neoplasia. This study was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Results: Three retrospective cohort studies involving 627 patients were included. Of these, 399 patients underwent RFA, and 228 were treated with cryotherapy. There was no difference in CE-IM (risk difference [RD], -0.03; 95% confidence interval [CI], -0.25 to 0.19; p=0.78; I²=86%) as well as in CE-D (RD, -0.03; 95% CI, -0.15 to 0.09; p=0.64; I²=70%) between the groups. The absolute number of adverse events was low, and there was no difference in the recurrence rate. Conclusions: Cryotherapy and RFA were equally effective in treating dysplastic BE, with or without early esophageal neoplasia.

• Journal of Internet Computing and Services
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• v.25 no.4
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• pp.109-119
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• 2024

This study aims to contribute to the initial research on on-device AI in an environment where generative AI-based services on mobile and other on-device platforms are increasing. To derive success strategies for generative AI-based chatbot services in a mobile environment, over 200,000 actual user experience review data collected from the Google Play Store were analyzed using the LDA topic modeling technique. Interpreting the derived topics based on the Information System Success Model (ISSM), the topics such as tutoring, limitation of response, and hallucination and outdated informaiton were linked to information quality; multimodal service, quality of response, and issues of device interoperability were linked to system quality; inter-device compatibility, utility of the service, quality of premium services, and challenges in account were linked to service quality; and finally, creative collaboration was linked to net benefits. Humanization of generative AI emerged as a new experience factor not explained by the existing model. By explaining specific positive and negative experience dimensions from the user's perspective based on theory, this study suggests directions for future related research and provides strategic insights for companies to improve and supplement their services for successful business operations.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.187-204
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• 2016

Document classification based on emotional polarity has become a welcomed emerging task owing to the great explosion of data on the Web. In the big data age, there are too many information sources to refer to when making decisions. For example, when considering travel to a city, a person may search reviews from a search engine such as Google or social networking services (SNSs) such as blogs, Twitter, and Facebook. The emotional polarity of positive and negative reviews helps a user decide on whether or not to make a trip. Sentiment analysis of customer reviews has become an important research topic as datamining technology is widely accepted for text mining of the Web. Sentiment analysis has been used to classify documents through machine learning techniques, such as the decision tree, neural networks, and support vector machines (SVMs). is used to determine the attitude, position, and sensibility of people who write articles about various topics that are published on the Web. Regardless of the polarity of customer reviews, emotional reviews are very helpful materials for analyzing the opinions of customers through their reviews. Sentiment analysis helps with understanding what customers really want instantly through the help of automated text mining techniques. Sensitivity analysis utilizes text mining techniques on text on the Web to extract subjective information in the text for text analysis. Sensitivity analysis is utilized to determine the attitudes or positions of the person who wrote the article and presented their opinion about a particular topic. In this study, we developed a model that selects a hot topic from user posts at China's online stock forum by using the k-means algorithm and self-organizing map (SOM). In addition, we developed a detecting model to predict a hot topic by using machine learning techniques such as logit, the decision tree, and SVM. We employed sensitivity analysis to develop our model for the selection and detection of hot topics from China's online stock forum. The sensitivity analysis calculates a sentimental value from a document based on contrast and classification according to the polarity sentimental dictionary (positive or negative). The online stock forum was an attractive site because of its information about stock investment. Users post numerous texts about stock movement by analyzing the market according to government policy announcements, market reports, reports from research institutes on the economy, and even rumors. We divided the online forum's topics into 21 categories to utilize sentiment analysis. One hundred forty-four topics were selected among 21 categories at online forums about stock. The posts were crawled to build a positive and negative text database. We ultimately obtained 21,141 posts on 88 topics by preprocessing the text from March 2013 to February 2015. The interest index was defined to select the hot topics, and the k-means algorithm and SOM presented equivalent results with this data. We developed a decision tree model to detect hot topics with three algorithms: CHAID, CART, and C4.5. The results of CHAID were subpar compared to the others. We also employed SVM to detect the hot topics from negative data. The SVM models were trained with the radial basis function (RBF) kernel function by a grid search to detect the hot topics. The detection of hot topics by using sentiment analysis provides the latest trends and hot topics in the stock forum for investors so that they no longer need to search the vast amounts of information on the Web. Our proposed model is also helpful to rapidly determine customers' signals or attitudes towards government policy and firms' products and services.

• Journal of The Korean Association For Science Education
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• v.34 no.3
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• pp.285-294
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• 2014

This study investigates the effects of formative assessment utilizing mobile applications on interest and self-directedness in science instruction. The study subjects are two 6th grade classes from H elementary school located in Incheon, and the experimental group and the comparative group are composed of 21 students, respectively. The students from the experimental group have been taught with mobile devices while the comparative group has been taught in methods consistent with the current teaching standards. For the sake of research, the results of the method applied to the mobile device focus group have been edited using Google Drive Forms, entered as QR codes and stored in order for them to later be utilized for teaching and learning process. In the process, the teacher has provided the students with feedback based on their answers. The students of comparative group are to solve the same formative assessment in paper. As a result, the teacher of the mobile device focus group has been able to go through twenty-nine questions on formative assessment in the teaching and learning process, confirm the correct answers five times and provide feedback twenty-five times for additional explanation. In the inquiry about interest, the mobile device group scored 4.64 points and the standard one scored just 1.99 points (p<0.01). Fifteen students answered in the interview that and the major reason why they scored high has been because it was fun to study with mobile devices. When it comes to self-directedness over the process of teaching and learning, the mobile device focus group has answered positively but the standard group has scored relatively low (p<0.01).

• Journal of the Korean earth science society
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• v.34 no.6
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• pp.515-523
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• 2013

The eastern coast of South Korea is expected to be damaged by volcanic ash when Mt. Baekdusan volcano erupts. Even if the amount of volcanic ash is small, it can be fatal on the agricultural sector withering many plants and causing soil acidification. Thus, in this paper, we aim to estimate agricultural losses caused by the volcanic ash and to visualize them with Google map. To estimate the volcanic ash losses, a damage assessment model is needed. As the volcanic ash hazard depends on the kind of a crops and the ash thickness, the fragility function of damage assessment model should represent the relation between ash thickness and damage rate of crops. Thus, we model the fragility function using the damage rate for each crop of RiskScape. The volcanic ash losses can be calculated with the agricultural output and the price of each crop using the fragility function. This paper also represents the estimated result of the losses in Gangwon province, which is most likely to get damaged by volcanic ashes in Korea. According to the result with gross agricultural output of Gangwon province in 2010, the amount of volcanic ash losses runs nearly 635,124 million wons in Korean currency if volcanic ash is accumulated over four millimeters. This amount represents about 50% of the gross agricultural output of Gangwon province. We consider the damage only for the crops in this paper. However, a volcanic ash fall has the potential to damage the assets for a farm, including the soil fertility and installations. Thus, to estimate the total amount of volcanic ash damage for the whole agricultural sectors, these collateral damages should also be considered.