• Korean Association of Arts Management
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• no.52
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• pp.75-105
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• 2019

In studying culture consumption today, it is essential to understand and analyze the actual visitors' experiences in detail. This is deeply related to the fact that we can utilize subjective experience records that were previously inaccessible as data since plenty of people actually record many performance experiences in the media space such as social media. This study attempts to examine what elements actually consists of people's performance experience based on actual expression of the performance experience that exists online. For this, we collected two types of data. First, we collected posts which required performance recommendation on online platforms such as Jisik-In and Cafes to see how people describe what they want and analyzed data focusing on the modifiers. Results show that people mainly use modifiers that reflect the specific situation of the individual such as companion or age. In addition we analyzed how the experience was described after the show through the review posts of ticket booking site. Results show how expressions are centered around companions, revisit intentions, and viewing experiences besides elements such as story and music, which have been known as main satisfaction elements of performance experience in previous studies. In addition, we discussed the practical implications and limitations of the study as well as the theoretical discussion.

• The Journal of the Korea Contents Association
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• v.20 no.11
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• pp.249-257
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• 2020

The study aims to explore whether the Supplier's social medial activities and the consumer's social media activities mediate between the characteristics of purchasing cosmetics and the intention of purchasing. To answer this question, a total of 321 consumers participated in the study, and a self-report type of questionnaires were utilized to collect the data. For the data analysis, descriptive statistical analysis and structural equation modeling(SEM) were applied. The results from the study are as follows. First, the characteristics of purchasing cosmetics did not affect the intention of purchasing cosmetics. Second, both the Supplier's and the consumer's social media activities positively predicted the intention of purchasing, among which the consumer's activities were ascertained to make more influential impact on the intention of purchasing cosmetics. Third, both Supplier's and consumer's social media activities completely mediated between the characteristics of purchasing cosmetics and the intention of purchasing. More discussions are suggested for marketing strategies in the study.

• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.409-418
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• 2015

With the development of mobile devices and Internet, information exchange has actively been made through SNS and Blogs. Blogs are widely used as a space where people share their experience after their visit to tourist attractions. We propose a method of recommending associated tourist attractions based on tourists' opinions using issue analysis, association analysis, and sentimental analysis for various online reviews including news in order to help to develop tour products and policies. The result shows that north area of Chungbuk province has been selected as issue attractions, and associated attractions/keywards have been identified for given well-known attraction. Positive/negative opinion for review texts has been analyzed and user can grasp the reason for the sentiments. Multidimensional analysis technique has been integrated to derive additional sophisticated insights and various policy proposal for smart tourism.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.9
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• pp.1153-1158
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• 2018

Online customer evaluations and social media information among a variety of information sources are critical for businesses as it influences the customer's decision making. There are limitations on the time and money that the survey will ask to identify a variety of customers' needs and complaints. The customer review data at online shopping malls provide the ideal data sources for analyzing customer sentiment about their products. In this study, we collected product reviews data on the smartphone of Samsung and Apple from Amazon. We applied five classification algorithms which are used as representative sentiment analysis techniques in previous studies. The five algorithms are based on support vector machines, bagging, random forest, classification or regression tree and maximum entropy. In this study, we proposed entropy score which can comprehensively evaluate the performance of classification algorithm. As a result of evaluating five algorithms using an entropy score, the SVMs algorithm's entropy score was ranked highest.

• Journal of Information Technology Services
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• v.19 no.5
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• pp.107-124
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• 2020

Due to spread of covid-19, which began in December 2019, the usage of online distance learning has expanded within colleges. However, because of the lack of readiness for running online distance learning, professors and students had to experience a lot of inconvenience. In the near future, the usage of online distance learnig is expected to more expand, thus, it seems that there should be a strategies for sustainable online learning operations. This study aims to investigate which factors have impact on the continuance intention to usage of online distance learning of airline department students, focused on Post-Acceptance Model. For the empirical analysis, this study utilized a structural equation model after collecting 136 survey data. The results is as follow; First, user interface has positive impact on confirmation and confirmation has positive impact on satisfaction of online distance learning. Seconds, confirmation has positive impact on perceived usefulness, flow and social presence. Third, social presence has positive impact on satisfaction of online distance learning, but perceived usefulness and flow didn't have statistically meaningful impact on satisfaction. Finally, statisfaction of online distance learning has huge positive impact on continuance intention to usage. It is expected that the implications of this study enable colleges effectively to run online distance learning in preparation for the post-covid 19 era.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.9
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• pp.1293-1304
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• 2022

The personalization recommendation system means analyzing each individual's interests or preferences and recommending information or products accordingly. These personalized recommendations can reduce the time consumers spend searching for information by accessing the products they need more quickly, and companies can increase corporate profits by recommending appropriate products that meet their needs. In this study, products are recommended to consumers using collaborative filtering, matrix factorization, and deep learning, which are representative personalization recommendation techniques. To this end, the data set after purchasing shopping mall products, which is raw data, is pre-processed in the form of transmitting the data set to the input of the recommended system, and the pre-processed data set is analyzed from various angles. In addition, each model performs verification and performance comparison on the recommended results, and explores the model with optimal performance, suggesting which model should be used when building the recommendation system at the mall.

• Science of Emotion and Sensibility
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• v.12 no.4
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• pp.433-442
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• 2009

People are tending to buy products through the Internet rather than purchasing them from the store. Some of the consumers give their feedback on line such as reviews, replies, comments, and blogs after they purchased the products. People are also likely to get some information through the Internet. Therefore, companies and public institutes have been facing this situation where they need to collect and analyze reviews or public opinions for them because many consumers are interested in other's opinions when they are about to make a purchase. However, most of the people's reviews on web site are too numerous, short and redundant. Under these circumstances, the emotion scanning system of text documents on the web is rising to the surface. Extracting writer's opinions or subjective ideas from text exists labeled words like GI(General Inquirer) and LKB(Lexical Knowledge base of near synonym difference) in English, however Korean language is not provided yet. In this paper, we labeled positive, negative, and neutral attribute at 4 POS(part of speech) which are noun, adjective, verb, and adverb in Korean dictionary. We extract construction patterns of emotional words and relationships among words in sentences from a large training set, and learned them. Based on this knowledge, comments and reviews regarding products are classified into two classes polarities with positive and negative using SO-PMI, which found the optimal condition from a combination of 4 POS. Lastly, in the design of the system, a flexible user interface is designed to add or edit the emotional words, the construction patterns related to emotions, and relationships among the words.

• Journal of Convergence for Information Technology
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• v.10 no.7
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• pp.84-97
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• 2020

This pilot study evaluated the reach and efficacy of nurse training program to provide palliative care to patients with advanced chronic diseases. A mixed method was used (an one-group pre-post research design and a group interview). To examine the changes in knowledge, attitude and self-efficacy, paired t-test were used with SPSS 21.0. To obtain pivoting information in real settings, a content analysis was conducted in the data obtaining from a group interview. There were significant improvements on knowledge and self-efficacy scores after the program. Additionally, high retention rate and program satisfaction were found in the participants while recruitment strategies, especially nurses working for tertiary hospitals, need to be modified in future research. A full-fledged research is warranted to find effective strategies to implement and disseminate the program for nurses working in diverse settings.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.190-198
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• 2022

In the food market, kiosks are rapidly expanding. The kiosk improves the in-store consumer experience and economic prosperity of businesses. This research explores the continuance use intention of kiosks via a post-acceptance model with four antecedent variables: perceived usefulness, perceived ease of use, confirmation, and satisfaction. An online survey was conducted with 420 senior consumers, aged 50-70, who have experienced kiosk services. This study used SPSS 25.0 for descriptive analysis and Amos 23.0 for confirmatory factor anlysis, structural equation analysis, and mediate the effect of the bootstrapping method. The following results were obtained. First, perceived usefulness and confirmation significantly influenced satisfaction with kiosks. Second, perceived usefulness and satisfaction significantly influenced continuance use intention. Third, satisfaction mediated the relationship between perceived usefulness and continuance use intention. Fourth, satisfaction mediated the relationship between confirmation and continuance use intention. These findings enhanced the understanding of seniors' attitude and response to kiosk services.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.289-305
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• 2023

The rapid increase in the use of mobile devices is changing consumers' online shopping behavior. However, the difference in the effect on the conversion rate according to the time when consumers switch from a small screen to a large screen has not been sufficiently studied. In addition, the differences in the effect of device conversion on purchase performance according to the characteristics of each country's infrastructure have not been sufficiently studied. Against this background, this study aims to analyze whether the timing of switching from mobile devices to PC devices and the country's mobile Internet penetration rate are moderating the positive effect of device switching on purchase performance. For empirical analysis, Google Merchandise Store data was collected and 101,466 data from 130 countries were analyzed with a multilevel model. As a result of the analysis, consumers' device switching (i.e., mobile to PC) had a positive effect when it occurred in the middle of the consumer journey. However, it was analyzed that when device switching occurred at the later stage of the consumer journey, it had a negative effect on purchase performance. In addition, it was analyzed that the higher the mobile Internet penetration rate, the weaker the positive effect of consumer device conversion on purchase performance.