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A Study on Visitor Engagement of the Audio Guide and Curating-bot at Museum of Modern and Contemporary Art

  • Bo-A Rhee;Ye-Eun Seo;Yeon-U Ro;Gyu-Hyun Kim
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.10
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    • pp.185-195
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    • 2024
  • In this paper, we propose a comparative evaluation framework for digital services in the Museum of Modern and Contemporary Art, focusing on user experience analysis of both mobile apps and curating-bots. Our method assesses the efficiency, support, and innovative attributes of these services, particularly regarding their Pragmatic Quality (PQ) and Hedonic Stimulation (HS). The proposed framework combines empirical user engagement data via survey with hypothesis testing to determine the influences of digital services such as the mobile app and curating-bot on visitor satisfaction and immersion. The research team demonstrates the suitability of the Technology Acceptance Model (TAM) and the Quality-Value-Loyalty (QVL) Chain in evaluating digital services in the art museum context and the impact of these services on the visitor experiences.

Current Status and Success Strategies of Crowdfunding for Start-up in Korea (국내 창업분야 크라우드펀딩(Crowdfunding) 현황과 성공전략)

  • Yoo, Younggeul;Jang, Ikhoon;Choe, Youngchan
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.9 no.4
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    • pp.1-12
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    • 2014
  • It is essential factor for business operation to raise funds effectively. However, in Korea, many start-ups and small businesses have difficulties in fund-raising. In recent years, crowdfunding, a new method for funding a project of individuals or organizations by raising monetary contributions from a large number of people, has been growing up simultaneously with diffusion of social media. Crowdfunding is on early stage in Korea, and the majority of projects are focused on cultural or art categories. There is high proportion of projects that have social value in start-up sector. Crowdfunding in Korea has great potential because success rate of it is much higher than its of advanced countries, although market size is much smaller than them. The purpose of this paper is to propose success strategies of crowdfunding for start-up through case study. 5 crowdfunding platforms of Korea and Kickstarter, the platform of United States were investigated. Then we checked the figures related to the operation of the whole Korean projects on start-up. Finally, we made comparison between the cases of success and failure by analyzing 8 project characteristics. The study shows that it were the differences in trustworthiness and activeness of project creator, value of reward and efforts for interactivity that have great effects on success of the project. Whereas there was no significant influence of societal contribution and sponsor engagement. The thesis provides success strategies of crowdfunding for start-up as follows. Firstly, creator of the project should make support base by enthusiastic activites before launching funding project. Secondly, there should be contents that can easily show the process of business development in the project information. Thirdly, there must be appropriate design of rewards for each amounts of support money. Finally, efforts for interactivity, such as frequent updates, response for comments and SNS posting, should be followed after the launch of the project.

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Improving the Accuracy of Document Classification by Learning Heterogeneity (이질성 학습을 통한 문서 분류의 정확성 향상 기법)

  • Wong, William Xiu Shun;Hyun, Yoonjin;Kim, Namgyu
    • Journal of Intelligence and Information Systems
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    • v.24 no.3
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    • pp.21-44
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    • 2018
  • In recent years, the rapid development of internet technology and the popularization of smart devices have resulted in massive amounts of text data. Those text data were produced and distributed through various media platforms such as World Wide Web, Internet news feeds, microblog, and social media. However, this enormous amount of easily obtained information is lack of organization. Therefore, this problem has raised the interest of many researchers in order to manage this huge amount of information. Further, this problem also required professionals that are capable of classifying relevant information and hence text classification is introduced. Text classification is a challenging task in modern data analysis, which it needs to assign a text document into one or more predefined categories or classes. In text classification field, there are different kinds of techniques available such as K-Nearest Neighbor, Naïve Bayes Algorithm, Support Vector Machine, Decision Tree, and Artificial Neural Network. However, while dealing with huge amount of text data, model performance and accuracy becomes a challenge. According to the type of words used in the corpus and type of features created for classification, the performance of a text classification model can be varied. Most of the attempts are been made based on proposing a new algorithm or modifying an existing algorithm. This kind of research can be said already reached their certain limitations for further improvements. In this study, aside from proposing a new algorithm or modifying the algorithm, we focus on searching a way to modify the use of data. It is widely known that classifier performance is influenced by the quality of training data upon which this classifier is built. The real world datasets in most of the time contain noise, or in other words noisy data, these can actually affect the decision made by the classifiers built from these data. In this study, we consider that the data from different domains, which is heterogeneous data might have the characteristics of noise which can be utilized in the classification process. In order to build the classifier, machine learning algorithm is performed based on the assumption that the characteristics of training data and target data are the same or very similar to each other. However, in the case of unstructured data such as text, the features are determined according to the vocabularies included in the document. If the viewpoints of the learning data and target data are different, the features may be appearing different between these two data. In this study, we attempt to improve the classification accuracy by strengthening the robustness of the document classifier through artificially injecting the noise into the process of constructing the document classifier. With data coming from various kind of sources, these data are likely formatted differently. These cause difficulties for traditional machine learning algorithms because they are not developed to recognize different type of data representation at one time and to put them together in same generalization. Therefore, in order to utilize heterogeneous data in the learning process of document classifier, we apply semi-supervised learning in our study. However, unlabeled data might have the possibility to degrade the performance of the document classifier. Therefore, we further proposed a method called Rule Selection-Based Ensemble Semi-Supervised Learning Algorithm (RSESLA) to select only the documents that contributing to the accuracy improvement of the classifier. RSESLA creates multiple views by manipulating the features using different types of classification models and different types of heterogeneous data. The most confident classification rules will be selected and applied for the final decision making. In this paper, three different types of real-world data sources were used, which are news, twitter and blogs.

The Construction of QoS Integration Platform for Real-time Negotiation and Adaptation Stream Service in Distributed Object Computing Environments (분산 객체 컴퓨팅 환경에서 실시간 협약 및 적응 스트림 서비스를 위한 QoS 통합 플랫폼의 구축)

  • Jun, Byung-Taek;Kim, Myung-Hee;Joo, Su-Chong
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.11S
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    • pp.3651-3667
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    • 2000
  • Recently, in the distributed multimedia environments based on internet, as radical growing technologies, the most of researchers focus on both streaming technology and distributed object thchnology, Specially, the studies which are tried to integrate the streaming services on the distributed object technology have been progressing. These technologies are applied to various stream service mamgements and protocols. However, the stream service management mexlels which are being proposed by the existing researches are insufficient for suporting the QoS of stream services. Besides, the existing models have the problems that cannot support the extensibility and the reusability, when the QoS-reiatedfunctions are being developed as a sub-module which is suited on the specific-purpose application services. For solving these problems, in this paper. we suggested a QoS Integrated platform which can extend and reuse using the distributed object technologies, and guarantee the QoS of the stream services. A structure of platform we suggested consists of three components such as User Control Module(UCM), QoS Management Module(QoSM) and Stream Object. Stream Object has Send/Receive operations for transmitting the RTP packets over TCP/IP. User Control ModuleI(UCM) controls Stream Objects via the COREA service objects. QoS Management Modulel(QoSM) has the functions which maintain the QoS of stream service between the UCMs in client and server. As QoS control methexlologies, procedures of resource monitoring, negotiation, and resource adaptation are executed via the interactions among these comiXments mentioned above. For constmcting this QoS integrated platform, we first implemented the modules mentioned above independently, and then, used IDL for defining interfaces among these mexlules so that can support platform independence, interoperability and portability base on COREA. This platform is constructed using OrbixWeb 3.1c following CORBA specification on Solaris 2.5/2.7, Java language, Java, Java Media Framework API 2.0, Mini-SQL1.0.16 and multimedia equipments. As results for verifying this platform functionally, we showed executing results of each module we mentioned above, and a numerical data obtained from QoS control procedures on client and server's GUI, while stream service is executing on our platform.

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Open Digital Textbook for Smart Education (스마트교육을 위한 오픈 디지털교과서)

  • Koo, Young-Il;Park, Choong-Shik
    • Journal of Intelligence and Information Systems
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    • v.19 no.2
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    • pp.177-189
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    • 2013
  • In Smart Education, the roles of digital textbook is very important as face-to-face media to learners. The standardization of digital textbook will promote the industrialization of digital textbook for contents providers and distributers as well as learner and instructors. In this study, the following three objectives-oriented digital textbooks are looking for ways to standardize. (1) digital textbooks should undertake the role of the media for blended learning which supports on-off classes, should be operating on common EPUB viewer without special dedicated viewer, should utilize the existing framework of the e-learning learning contents and learning management. The reason to consider the EPUB as the standard for digital textbooks is that digital textbooks don't need to specify antoher standard for the form of books, and can take advantage od industrial base with EPUB standards-rich content and distribution structure (2) digital textbooks should provide a low-cost open market service that are currently available as the standard open software (3) To provide appropriate learning feedback information to students, digital textbooks should provide a foundation which accumulates and manages all the learning activity information according to standard infrastructure for educational Big Data processing. In this study, the digital textbook in a smart education environment was referred to open digital textbook. The components of open digital textbooks service framework are (1) digital textbook terminals such as smart pad, smart TVs, smart phones, PC, etc., (2) digital textbooks platform to show and perform digital contents on digital textbook terminals, (3) learning contents repository, which exist on the cloud, maintains accredited learning, (4) App Store providing and distributing secondary learning contents and learning tools by learning contents developing companies, and (5) LMS as a learning support/management tool which on-site class teacher use for creating classroom instruction materials. In addition, locating all of the hardware and software implement a smart education service within the cloud must have take advantage of the cloud computing for efficient management and reducing expense. The open digital textbooks of smart education is consdered as providing e-book style interface of LMS to learners. In open digital textbooks, the representation of text, image, audio, video, equations, etc. is basic function. But painting, writing, problem solving, etc are beyond the capabilities of a simple e-book. The Communication of teacher-to-student, learner-to-learnert, tems-to-team is required by using the open digital textbook. To represent student demographics, portfolio information, and class information, the standard used in e-learning is desirable. To process learner tracking information about the activities of the learner for LMS(Learning Management System), open digital textbook must have the recording function and the commnincating function with LMS. DRM is a function for protecting various copyright. Currently DRMs of e-boook are controlled by the corresponding book viewer. If open digital textbook admitt DRM that is used in a variety of different DRM standards of various e-book viewer, the implementation of redundant features can be avoided. Security/privacy functions are required to protect information about the study or instruction from a third party UDL (Universal Design for Learning) is learning support function for those with disabilities have difficulty in learning courses. The open digital textbook, which is based on E-book standard EPUB 3.0, must (1) record the learning activity log information, and (2) communicate with the server to support the learning activity. While the recording function and the communication function, which is not determined on current standards, is implemented as a JavaScript and is utilized in the current EPUB 3.0 viewer, ths strategy of proposing such recording and communication functions as the next generation of e-book standard, or special standard (EPUB 3.0 for education) is needed. Future research in this study will implement open source program with the proposed open digital textbook standard and present a new educational services including Big Data analysis.

Analysis of the Work of the Head Nurse and a Work Model for the Head Nurse in University Hospitals in Korea (대학종합병원 수간호사의 업무분석과 모형연구)

  • 김인숙
    • Journal of Korean Academy of Nursing
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    • v.19 no.2
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    • pp.212-222
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    • 1989
  • When the head nurse who is pivotal in the nursing service administration of the hospital performs efficiently as a first-line manager, the effectiveness of the nursing unit, which includes the quality of nursing care, the jab satisfaction of staff members, and the cohesiveness of staff members is increased. With this point of view in mind, the researcher carried out a study to determine the actual work (the content of the work, the work process, the role of the head nurse, the activity media, and the purpose of the work) of the head nurse in a university hospital in Korea. In addition, this study was also carried out for the purpose of preparing an ideal model for the work of the head nurse. The research subjects were 39 head nurses. This included all the head nurses in two university hospitals except those who were working in outpatient care, operating rooms, central supply, nursing administration, in-service education and emergency care. Data were collected from September 24th to October 21th, 1987 and April 4th to 12th, 1988. A work activity record on which the head nurse recorded directly in a chronological narrative form, was used as the research instrument. The 234 work activity records, 39 head nurse's continuous recording over 6 days(from Monday to Saturday) were collected and analysed. The results were as follows ; 1. With regard to the work content for the total daily work of the head nurse, 45.2% of the activities were managerial activities but 58.1% of the head nurse' s time was spent in direct patient care. 2. With regard to the work process of the head nurse, specifically the location, the size and membership of groups contacted, the results were as follows : 1) Of the total daily work activities 92.4% were carried out in the nursing unit and this occupied 84.5% of total daily work time. Direct patient care was generally performed on the nursing unit and managerial work was performed in other areas. 2) Of the total daily work activities, 73% was with one or more persons and 51.2% of total daily work time was spent in groups. 3) A total of 51 persons, working in different capacities were contacted. These included 21 persons giving patient care, 19 persons working in nursing unit management, and 7 persons working in human resource management. 3. With regard to the head nurse's role in work activity, 53.3% of total daily work activities involved the informational role, 26.9%, the interpersonal role and 19.9%, the decisional role. With regard to time, 57.7% was spent in the informational role, 23.9%, in the interpersonal role and 18.3%, in the decisional role. When the head nurse performed managerial work, she gave nearly equal emphasis to all three roles when she gave direct patient care the informational role was increased. 4. With regard to the activity media, the number of unscheduled activities accounted for 27.1% of the activities, scheduled activities, 24.3%, desk work activity, 22.1%, rounds, 12.5% and telephone calls, made or received, 14.0%. In daily total work time managerial work related to desk work and scheduled activities were high, ranging from 29.8% to 29.9% but for direct patient care time, scheduled activities and unscheduled activities were high, ranging from 23.6% to 35.3%. 5. With regard to the purpose of the work performed, 54.4% of the total daily work was concerned with the team and 41.4% was concerned with the agency. The managerial work was concerned mainly with the team and the direct patient care was concerned mainly with the patient. When the frequency of an activity and time were compared no significant difference was found between the days for which the work was recorded for any of the variables : the work content, the work process, the work role, the activity media and purpose of the work. On the basis of this study the following are proposed as an ideal model for head nurse work in Korea : The managerial work should be increased to 70%. The decisional role activities should be increased to 40%. Twenty percent of the work activity should be allocated to agency, community and profession. It is believed that this model for the head nurse's work can contribute to guidelines for job description development. Finally, educational programs, organizational and structural devices, and administrative support are needed for the proper function of the head nurse in this proposed model.

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Building a Korean Sentiment Lexicon Using Collective Intelligence (집단지성을 이용한 한글 감성어 사전 구축)

  • An, Jungkook;Kim, Hee-Woong
    • Journal of Intelligence and Information Systems
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    • v.21 no.2
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    • pp.49-67
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    • 2015
  • Recently, emerging the notion of big data and social media has led us to enter data's big bang. Social networking services are widely used by people around the world, and they have become a part of major communication tools for all ages. Over the last decade, as online social networking sites become increasingly popular, companies tend to focus on advanced social media analysis for their marketing strategies. In addition to social media analysis, companies are mainly concerned about propagating of negative opinions on social networking sites such as Facebook and Twitter, as well as e-commerce sites. The effect of online word of mouth (WOM) such as product rating, product review, and product recommendations is very influential, and negative opinions have significant impact on product sales. This trend has increased researchers' attention to a natural language processing, such as a sentiment analysis. A sentiment analysis, also refers to as an opinion mining, is a process of identifying the polarity of subjective information and has been applied to various research and practical fields. However, there are obstacles lies when Korean language (Hangul) is used in a natural language processing because it is an agglutinative language with rich morphology pose problems. Therefore, there is a lack of Korean natural language processing resources such as a sentiment lexicon, and this has resulted in significant limitations for researchers and practitioners who are considering sentiment analysis. Our study builds a Korean sentiment lexicon with collective intelligence, and provides API (Application Programming Interface) service to open and share a sentiment lexicon data with the public (www.openhangul.com). For the pre-processing, we have created a Korean lexicon database with over 517,178 words and classified them into sentiment and non-sentiment words. In order to classify them, we first identified stop words which often quite likely to play a negative role in sentiment analysis and excluded them from our sentiment scoring. In general, sentiment words are nouns, adjectives, verbs, adverbs as they have sentimental expressions such as positive, neutral, and negative. On the other hands, non-sentiment words are interjection, determiner, numeral, postposition, etc. as they generally have no sentimental expressions. To build a reliable sentiment lexicon, we have adopted a concept of collective intelligence as a model for crowdsourcing. In addition, a concept of folksonomy has been implemented in the process of taxonomy to help collective intelligence. In order to make up for an inherent weakness of folksonomy, we have adopted a majority rule by building a voting system. Participants, as voters were offered three voting options to choose from positivity, negativity, and neutrality, and the voting have been conducted on one of the largest social networking sites for college students in Korea. More than 35,000 votes have been made by college students in Korea, and we keep this voting system open by maintaining the project as a perpetual study. Besides, any change in the sentiment score of words can be an important observation because it enables us to keep track of temporal changes in Korean language as a natural language. Lastly, our study offers a RESTful, JSON based API service through a web platform to make easier support for users such as researchers, companies, and developers. Finally, our study makes important contributions to both research and practice. In terms of research, our Korean sentiment lexicon plays an important role as a resource for Korean natural language processing. In terms of practice, practitioners such as managers and marketers can implement sentiment analysis effectively by using Korean sentiment lexicon we built. Moreover, our study sheds new light on the value of folksonomy by combining collective intelligence, and we also expect to give a new direction and a new start to the development of Korean natural language processing.

Suggestion of Similarity-Based Representative Odor for Video Reality (영상실감을 위한 유사성 기반 대표냄새 사용의 제안)

  • Lee, Guk-Hee;Choi, Ji Hoon;Ahn, Chung Hyun;Li, Hyung-Chul O.;Kim, ShinWoo
    • Science of Emotion and Sensibility
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    • v.17 no.1
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    • pp.39-52
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    • 2014
  • Use of vision and audition for video reality has made much advancement. However use of olfaction, which is effective in inducing emotion, has not yet been realized due to technical limitations and lack of basic research. In particular it is difficult to fabricate many odors required for each different video. One way to resolve this is to discover clusters of odors of similar smell and to use representative odor for each cluster. This research explored clusters of odors based on pairwise similarity ratings. 300 diverse odors were first collected and sorted them into 11 categories. We selected 152 odors based on their frequency, preference, and concreteness. Participants rated similarity on 1,018 pairs of odors from selected odors and the results were analyzed using multi-dimensional scaling (MDS). Based on the idea that low odor concreteness would support valid use of representative odor, the MDS results are presented from low to high smell concreteness. First, flowers, plants, fruits, and vegetables was classified under the easy categories to use representative odor due to their low smell concreteness (Figure 1). Second, chemicals, personal cares, physiological odors, and ordinary places was classified under the careful categories of using it due to their intermediate concreteness (Figure 2). Finally, food ingredients, beverages, and foods was classified under the difficult categories to use it because of their high concreteness (Figure 3). The results of this research will contribute to reduction of cost and time in odor production and provision of realistic media service to customers at reasonable price.

Designing an Intelligent Advertising Business Model in Seoul's Metro Network (서울지하철의 지능형 광고 비즈니스모델 설계)

  • Musyoka, Kavoya Job;Lim, Gyoo Gun
    • Journal of Intelligence and Information Systems
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    • v.23 no.4
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    • pp.1-31
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    • 2017
  • Modern businesses are adopting new technologies to serve their markets better as well as to improve efficiency and productivity. The advertising industry has continuously experienced disruptions from the traditional channels (radio, television and print media) to new complex ones including internet, social media and mobile-based advertising. This case study focuses on proposing intelligent advertising business model in Seoul's metro network. Seoul has one of the world's busiest metro network and transports a huge number of travelers on a daily basis. The high number of travelers coupled with a well-planned metro network creates a platform where marketers can initiate engagement and interact with both customers and potential customers. In the current advertising model, advertising is on illuminated and framed posters in the stations and in-car, non-illuminated posters, and digital screens that show scheduled arrivals and departures of metros. Some stations have digital screens that show adverts but they do not have location capability. Most of the current advertising media have one key limitation: space. For posters whether illuminated or not, one space can host only one advert at a time. Empirical literatures show that there is room for improving this advertising model and eliminate the space limitation by replacing the poster adverts with digital advertising platform. This new model will not only be digital, but will also provide intelligent advertising platform that is driven by data. The digital platform will incorporate location sensing, e-commerce, and mobile platform to create new value to all stakeholders. Travel cards used in the metro will be registered and the card scanners will have a capability to capture traveler's data when travelers tap their cards. This data once analyzed will make it possible to identify different customer groups. Advertisers and marketers will then be able to target specific customer groups, customize adverts based on the targeted consumer group, and offer a wide variety of advertising formats. Format includes video, cinemagraphs, moving pictures, and animation. Different advert formats create different emotions in the customer's mind and the goal should be to use format or combination of formats that arouse the expected emotion and lead to an engagement. Combination of different formats will be more effective and this can only work in a digital platform. Adverts will be location based, ensuring that adverts will show more frequently when the metro is near the premises of an advertiser. The advertising platform will automatically detect the next station and screens inside the metro will prioritize adverts in the station where the metro will be stopping. In the mobile platform, customers who opt to receive notifications will receive them when they approach the business premises of advertiser. The mobile platform will have indoor navigation for the underground shopping malls that will allow customers to search for facilities within the mall, products they may want to buy as well as deals going on in the underground mall. To create an end-to-end solution, the mobile solution will have a capability to allow customers purchase products through their phones, get coupons for deals, and review products and shops where they have bought a product. The indoor navigation will host intelligent mobile-based advertisement and a recommendation system. The indoor navigation will have adverts such that when a customer is searching for information, the recommendation system shows adverts that are near the place traveler is searching or in the direction that the traveler is moving. These adverts will be linked to the e-commerce platform such that if a customer clicks on an advert, it leads them to the product description page. The whole system will have multi-language as well as text-to-speech capability such that both locals and tourists have no language barrier. The implications of implementing this model are varied including support for small and medium businesses operating in the underground malls, improved customer experience, new job opportunities, additional revenue to business model operator, and flexibility in advertising. The new value created will benefit all the stakeholders.

Analysis of News Agenda Using Text mining and Semantic Network Analysis: Focused on COVID-19 Emotions (텍스트 마이닝과 의미 네트워크 분석을 활용한 뉴스 의제 분석: 코로나 19 관련 감정을 중심으로)

  • Yoo, So-yeon;Lim, Gyoo-gun
    • Journal of Intelligence and Information Systems
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    • v.27 no.1
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    • pp.47-64
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    • 2021
  • The global spread of COVID-19 around the world has not only affected many parts of our daily life but also has a huge impact on many areas, including the economy and society. As the number of confirmed cases and deaths increases, medical staff and the public are said to be experiencing psychological problems such as anxiety, depression, and stress. The collective tragedy that accompanies the epidemic raises fear and anxiety, which is known to cause enormous disruptions to the behavior and psychological well-being of many. Long-term negative emotions can reduce people's immunity and destroy their physical balance, so it is essential to understand the psychological state of COVID-19. This study suggests a method of monitoring medial news reflecting current days which requires striving not only for physical but also for psychological quarantine in the prolonged COVID-19 situation. Moreover, it is presented how an easier method of analyzing social media networks applies to those cases. The aim of this study is to assist health policymakers in fast and complex decision-making processes. News plays a major role in setting the policy agenda. Among various major media, news headlines are considered important in the field of communication science as a summary of the core content that the media wants to convey to the audiences who read it. News data used in this study was easily collected using "Bigkinds" that is created by integrating big data technology. With the collected news data, keywords were classified through text mining, and the relationship between words was visualized through semantic network analysis between keywords. Using the KrKwic program, a Korean semantic network analysis tool, text mining was performed and the frequency of words was calculated to easily identify keywords. The frequency of words appearing in keywords of articles related to COVID-19 emotions was checked and visualized in word cloud 'China', 'anxiety', 'situation', 'mind', 'social', and 'health' appeared high in relation to the emotions of COVID-19. In addition, UCINET, a specialized social network analysis program, was used to analyze connection centrality and cluster analysis, and a method of visualizing a graph using Net Draw was performed. As a result of analyzing the connection centrality between each data, it was found that the most central keywords in the keyword-centric network were 'psychology', 'COVID-19', 'blue', and 'anxiety'. The network of frequency of co-occurrence among the keywords appearing in the headlines of the news was visualized as a graph. The thickness of the line on the graph is proportional to the frequency of co-occurrence, and if the frequency of two words appearing at the same time is high, it is indicated by a thick line. It can be seen that the 'COVID-blue' pair is displayed in the boldest, and the 'COVID-emotion' and 'COVID-anxiety' pairs are displayed with a relatively thick line. 'Blue' related to COVID-19 is a word that means depression, and it was confirmed that COVID-19 and depression are keywords that should be of interest now. The research methodology used in this study has the convenience of being able to quickly measure social phenomena and changes while reducing costs. In this study, by analyzing news headlines, we were able to identify people's feelings and perceptions on issues related to COVID-19 depression, and identify the main agendas to be analyzed by deriving important keywords. By presenting and visualizing the subject and important keywords related to the COVID-19 emotion at a time, medical policy managers will be able to be provided a variety of perspectives when identifying and researching the regarding phenomenon. It is expected that it can help to use it as basic data for support, treatment and service development for psychological quarantine issues related to COVID-19.