• Journal of the Korean Society for information Management
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• v.39 no.1
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• pp.91-117
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• 2022

The number of depressed patients in Korea and around the world is rapidly increasing every year. However, most of the mentally ill patients are not aware that they are suffering from the disease, so adequate treatment is not being performed. If depressive symptoms are neglected, it can lead to suicide, anxiety, and other psychological problems. Therefore, early detection and treatment of depression are very important in improving mental health. To improve this problem, this study presented a deep learning-based depression tendency model using Korean social media text. After collecting data from Naver KonwledgeiN, Naver Blog, Hidoc, and Twitter, DSM-5 major depressive disorder diagnosis criteria were used to classify and annotate classes according to the number of depressive symptoms. Afterwards, TF-IDF analysis and simultaneous word analysis were performed to examine the characteristics of each class of the corpus constructed. In addition, word embedding, dictionary-based sentiment analysis, and LDA topic modeling were performed to generate a depression tendency classification model using various text features. Through this, the embedded text, sentiment score, and topic number for each document were calculated and used as text features. As a result, it was confirmed that the highest accuracy rate of 83.28% was achieved when the depression tendency was classified based on the KorBERT algorithm by combining both the emotional score and the topic of the document with the embedded text. This study establishes a classification model for Korean depression trends with improved performance using various text features, and detects potential depressive patients early among Korean online community users, enabling rapid treatment and prevention, thereby enabling the mental health of Korean society. It is significant in that it can help in promotion.

• Journal of Korean Clinical Nursing Research
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• v.22 no.2
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• pp.173-182
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• 2016

Purpose: This study investigated the linking words of nurse which were presented together with nurse on phrase, clauses or sentence of documents or conversations in the Internet portals and social media. Methods: The linking words with nurse were calculated by the number of presentation on conversations or documents, in Google, Daum, Naver, Twitter and Facebook. The changes of characteristics and the trend of yearly changes of major linking words of nurse were investigated by the type of media. In order to identify the meaning of the words, clustering of the collected linking words by categories was analysed and the characteristics of each cluster were classified. Results: A total number of reviewed linking words was 17,399,711 and the most frequently presenting words were hospital, work and person. The words related to people were the most highly presented and the next were those of emotion, professional and place respectively. Conclusion: With analysing the trends of changes and characteristics of words by yearly base and clusters, we attempted to investigate the image of nurse that the public think and feel about nurse.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.263-266
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• 2013

The universal cloud computing environment, the increase of mobile devices, and the emergence of various web-based services require large amounts of storage space. With the widespread use of Web-based storage services, such as Google Drive, Naver Ndrive, Daum Cloud, there is a need for more storage space. Therefore, storage areas can be provided according to the needs of users of virtualized storage resources through a network, and a large, easy to extend, and royalty in a specific geographical location, cloud storage may be the limelight. In this paper, find out about the features of open source software technology, Hadoop, Swift, GlusterFS for Cloud Storage infrastructure.

• Journal of the Korean Society of Clothing and Textiles
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• v.41 no.6
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• pp.1022-1038
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• 2017

Wearable smart products contributed to expand the concept of modern clothing in terms of closer communication between wearers and the surrounding environment. This study investigated the concept of wearable smart actuators and characteristics of actuating feedback. The representative product development trends over the past 10 years are examined based on the method of actuating feedback. A first keyword search from Naver and Google reused to select the final 58 products based on the second key keyword actuating feedback. The wearable smart actuator system works in a similar way to a human body system such as those of the information processing process. Actuating feedback is delivered directly to the user as the last signal of the system, which has visual, auditory and tactile feedback. It works in complex at the device to be delivered to the user. Actuator feedback is divided into three types of active and passive, depending on the user situation, the overall purpose of the product, the collected information, and the device dependency. Active actuating feedback determines and actuates the situation on behalf of the user when the user is in an emergency or a disability situation. Passive actuating feedback plays a role in environmental monitoring to help in a healthy daily life.

• The Journal of Society for e-Business Studies
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• v.25 no.4
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• pp.125-141
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• 2020

Recent Studies emphasize the effect of investors attention, recognition and sentiment on the trading behavior of retail investors and stock price variation. In this study, we use Naver Trend to measure investors'attention and investigate the relation between investor attention and price synchronicity, total risk and systematic risk of stocks. Using various research methodologies such as portfolio analysis, fixed effect regression and dynamic panel analysis, we find consistent results. First, stock price synchronicity is increased with lager average search volume, but with less search variability. Second, both average search volume and its variability are positively related to total risk and beta of stocks. These results can be interpreted that search volume sharply increases only when stock-related event occurs.

• The Journal of Society for e-Business Studies
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• v.22 no.2
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• pp.153-168
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• 2017

Recent studies focus on the role of investor attention and transparency in stock-related information in explaining stock return and trading volume. Moreover, recent literatures predict that firm opacity will increase the likelihood of future stock price crashes. In this paper, we investigate, using Naver Trend, the relation between portal search intensity and stock price crash. Using various alternative measures of stock price crash risk and search intensity, we demonstrate that stocks with larger volume of portal search are less likely to experience stock price crashes. These results are consistent with our hypothesis that accumulated firm opacity cause future stock price crash. Finally, our results still hold even after we control for the potential effect of endogeneity in the regression specifications.

• Journal of the Korean Dietetic Association
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• v.14 no.3
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• pp.218-228
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• 2008

This study was conducted to evaluate the quantitative and qualitative aspects of Korean websites related to nutrition education. A total of 30 websites were ultimately selected through 4 major Internet search engines, including Naver, Yahoo, Daum, and Nate, using several key words (i.e., nutrition education, dietary life education, nutrition information, nutrition management, etc.). A systematic review was conducted for each of the selected websites based on the American Library Association (ALA) website checklist and a data abstract form that was adapted from a previous study. Approximately two thirds of the websites were established between 2002 and 2005, and 46.6% were administrated by public health centers or schools/colleges. The most frequently targeted group was the generally healthy population (30.0%). Among the various topics of nutrition information provided, “balanced diet” was the topic most often provided by the websites. Also, an increasing trend for utilizing multimedia tools was observed; however, little technical support or instruction was provided by the websites. Only 50.0% and 63.3% of the sites clearly stated their operators and sources of provided information, respectively. Overall, the purposes of sites were clearly stated, and were not overshadowed by advertising. And most features of design, stability, and content were found to be appropriate, but several aspects, such as establishing a help/FAQ menu, regularly updating nutrition information, and converting provided information into a database for easier search and update, needed improvement. In addition, active operational strategies are greatly needed to encourage the application of materials found on sites into real educational settings.

• Fashion & Textile Research Journal
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• v.15 no.5
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• pp.694-703
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• 2013

A variable dress design can be an alternative to satisfy a consumer need for diverse expression and self-realization at a lower cost factor. In the area of wedding dress, the change in the trend of wedding culture (which tends to demand more units of wedding dress) makes the cost factor more important in the purchase selection. A variable design has a clear advantage for wedding dresses and the wedding industry. This is the first research on a variable design that focuses on wedding dresses. This research develops a variable wedding design which respects consumer preferences independent of a variable wedding dress design that presents a new shape of silhouette or the development ofa new wedding dress materials. A survey on the supply side was conducted to examine market preferences by first browsing the Naver portal site and then checking the websites of major wedding dress suppliers. A questionnaire survey was conducted with a sample of 348 brides-to-be that inquired on wedding dress selection factors and purchase patterns. The survey shows that consumers prefer mermaid and A-line silhouettes, silk material, white-ivory color, and tube top necklines. The result conforms to the types commonly found in the designs of suppliers. We apply a detachable design to a basic mermaid silhouette and implemented change for 7 kinds of styles -based on the result of the survey. We suggest a variable wedding dress design as a new means to solve the cost concern and the customer need for diverse expression. The research represents a new life style for wedding culture and facilitates the development of the wedding industry.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.4
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• pp.739-746
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• 2020

The fourth industrial revolution introduced at world economic forum in 2016 has had huge effects on tourism industries as well as the change of core technologies in ICT such as big data, IoT, etc, This paper proposes the methods to propel tourism of Yoesu city through big data analysis and questionnaires. Sensitive words and positive-negative trend are extracted by Social Metrics and the keywords for Yeosu tour trends are extracted and analyzed by Naver datalab, and the results are visualized by R language. And frequency, difference, factor, covariance and regression analysis in SPSS are executed for the questionnaires for 493 visitors who traveled in Yeosu city. Sentiment analysis for Yeosu tour and maritime cable car shows that positive effect is much more than negative one. The analyses for questionnaires in SPSS show that Yeosu area is statistically significant to tour satisfaction index and tour revitalization for Yeosu, and favorite sightseeing places and searching electronic devices for age groups are different. The sightseeing places such as a maritime park with soft contents that give joyfulness and healing to tourists are highly attracted in both the big data and questionnaires analysis.

• Journal of the Korean Society of Clothing and Textiles
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• v.40 no.6
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• pp.1034-1044
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• 2016

This study seeks a method to objectively evaluate sensibility based on Big Data in the field of design. In order to do so, this study examined the sensibility responses on design factors for the public through a network analysis of texts displayed in social media. 'Hanbok', a formal clothing that represents Korea, was selected as the subject for the research methodology. We then collected 47,677 keywords related to Hanbok from 12,000 posts on Naver blogs from January $1^{st}$ to December $31^{st}$ 2015 and that analyzed using social matrix (a Big Data analysis software) rather than using previous survey methods. We also derived 56 key-words related to design elements and sensibility responses of Hanbok. Centrality analysis and CONCOR analysis were conducted using Ucinet6. The visualization of the network text analysis allowed the categorization of the main design factors of Hanbok with evaluation terms that mean positive, negative, and neutral sensibility responses. We also derived key evaluation factors for Hanbok as fitting, rationality, trend, and uniqueness. The evaluation terms extracted based on natural language processing technologies of atypical data have validity as a scale for evaluation and are expected to be suitable for utilization in an index for sensibility evaluation that supplements the limits of previous surveys and statistical analysis methods. The network text analysis method used in this study provides new guidelines for the use of Big Data involving sensibility evaluation methods in the field of design.