• Human Ecology Research
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• v.59 no.1
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• pp.23-43
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• 2021

This study looked through the text mining analysis to check the status of the virtual assistant service, and explore the needs of consumers, and present consumer-oriented directions. Trendup 4.0 was used to analyze the keywords of AI services in Online News and social media from 2016 to 2020. The R program was used to collect consumer comment data and implement Topic Modeling analysis. According to the analysis, the number of mentions of AI services in mass media and social media has steadily increased. The Sentimental Analysis showed consumers were feeling positive about AI services in terms of useful and convenient functional and emotional aspects such as pleasure and interest. However, consumers were also experiencing complexity and difficulty with AI services and had concerns and fears about the use of AI services in the early stages of their introduction. The results of the consumer review analysis showed that there were topics(Technical Requirements) related to technology and the access process for the AI services to be provided, and topics (Consumer Request) expressed negative feelings about AI services, and topics(Consumer Life Support Area) about specific functions in the use of AI services. Text mining analysis enable this study to confirm consumer expectations or concerns about AI service, and to examine areas of service support that consumers experienced. The review data on each platform also revealed that the potential needs of consumers could be met by expanding the scope of support services and applying platform-specific strengths to provide differentiated services.

• Journal of Korean Academy of Nursing
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• v.47 no.6
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• pp.806-816
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• 2017

Purpose: As comprehensive nursing care service has gradually expanded, it has become necessary to explore the various opinions about it. The purpose of this study is to explore the large amount of text data regarding comprehensive nursing care service extracted from online news and social media by applying a semantic network analysis. Methods: The web pages of the Korean Nurses Association (KNA) News, major daily newspapers, and Twitter were crawled by searching the keyword 'comprehensive nursing care service' using Python. A morphological analysis was performed using KoNLPy. Nodes on a 'comprehensive nursing care service' cluster were selected, and frequency, edge weight, and degree centrality were calculated and visualized with Gephi for the semantic network. Results: A total of 536 news pages and 464 tweets were analyzed. In the KNA News and major daily newspapers, 'nursing workforce' and 'nursing service' were highly rated in frequency, edge weight, and degree centrality. On Twitter, the most frequent nodes were 'National Health Insurance Service' and 'comprehensive nursing care service hospital.' The nodes with the highest edge weight were 'national health insurance,' 'wards without caregiver presence,' and 'caregiving costs.' 'National Health Insurance Service' was highest in degree centrality. Conclusion: This study provides an example of how to use atypical big data for a nursing issue through semantic network analysis to explore diverse perspectives surrounding the nursing community through various media sources. Applying semantic network analysis to online big data to gather information regarding various nursing issues would help to explore opinions for formulating and implementing nursing policies.

• The Journal of Asian Finance, Economics and Business
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• v.5 no.2
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• pp.95-104
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• 2018

The purpose of this study is to investigate the impact of narcissism on employees' social media addiction and how it influences their job satisfaction and organizational commitment. And this study explores if perceived organizational support can moderate the relationship between narcissism and social media addiction. For this, this study collected data from 285 employees in Korean companies through a survey method and uses SPSS 18.0 for hierarchical regression analysis in the hypothesis test. First, organizational politics increases mood modification, withdrawal and tolerance among the sub-factors of social media addiction. Second, each phenomena of social media service addiction such as salience, withdrawal and tolerance decrease each relevant factors of job satisfaction and organizational commitment. Third, withdrawal and tolerance among the sub-factors of social media addiction play the mediating roles between narcissism and each relevant factors of job satisfaction/organizational commitment. Finally, perceived organizational support decrease the effect of narcissism on mood modification, withdrawal and tolerance among the sub-factors of social media addiction. This study provides some of managerial implications to corporate executives who try to manage organizational attitudes.

• Journal of Information Technology Applications and Management
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• v.22 no.2
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• pp.123-148
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• 2015

Today the mobile devices including smart phones have influenced on the users' daily activities in the mobile internet society, and the expansion of social media has also affected on the purchasing behavior of consumers. This study examines whether the quality of corporate twitter, a typical social network service for call centers influences on the customer satisfaction, and brand loyalty. In order to achieve the research goal, the quality of twitter has been divided into four variables; information quality, service quality, system quality, and social quality. The results of our empirical analysis show that the three variables except service quality have significantly influenced on the customer satisfaction and the customer satisfaction also significantly has a casual effect on the brand loyalty. The empirical results are expected as a guideline to contribute on the practical improvement of customer service, satisfaction, and brand loyalty through corporate social network services such as corporate twitters in the future.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.163-170
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• 2021

As a big data is being used in various industries, big data market is expanding from hardware to infrastructure software to service software. Especially it is expanding into a huge platform market that provides applications for holistic and intuitive visualizations such as big data meaning interpretation understandability, and analysis results. Demand for big data extraction and analysis using social media such as SNS is very active not only for companies but also for individuals. However despite such high demand for the collection and analysis of social media data for user trend analysis and marketing, there is a lack of research to address the difficulty of dynamic interlocking and the complexity of building and operating software platforms due to the heterogeneity of various social media service interfaces. In this paper, we propose a method for developing a framework to operate the process from collection to extraction and classification of social media data. The proposed framework solves the problem of heterogeneous social media data collection channels through adapter patterns, and improves the accuracy of social topic extraction and classification through semantic association-based extraction techniques and topic association-based classification techniques.

• Journal of Korean Society of Archives and Records Management
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• v.22 no.2
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• pp.1-25
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• 2022

Today, most archives provide recording services through social media; however, their effectiveness is very low. This study aimed to analyze the causes of insufficient social media recording service, focusing on Gyeongnam Archives and Seoul Metropolitan Archives, which are permanent records management institutions and local government archives, and design ways to create synergy by mutual growth with classical recording service. Through literature research, the characteristics and mechanisms of each social medium were identified, and the institutions' current status of social media operations and internal documents were reviewed to analyze the common problems. An in-depth analysis was conducted by interviewing the person in charge of recording services at each institution. In addition, a plan that can be applied to archives was proposed by reviewing the cases of social media operations of domestic-related institutions and overseas archives. Based on this, a new recording service process was established, strategic operation plans for each social medium were proposed, and a plan to mutually grow with the existing recording service was designed.

• Journal of the Korea Society of Computer and Information
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• v.21 no.8
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• pp.105-116
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• 2016

Corporate social media has been recently used in customer relationship management in many ways to improve product sales and company images. Not much research exists on corporate social media, Therefore, in this paper, we propose a research model to identify how corporate social media enhances corporate's CRM quality, resulting in forming customer's purchase intention. In detail, this paper is to examine how customer's perceived value of corporate social media influences CRM quality(CRM trust and CRM commitment), and then how CRM quality affects purchase intention. To this end, a total of 300 questionnaires were used from online panel respondents to test research hypothesis. The findings showed that service performance value and monetary value were major determinants of CRM trust, however, there was no association between brand integration value and CRM trust. In addition, the effects of service performance value and brand integration value on CRM commitment were found whereas monetary value had no effect on CRM commitment. The results also showed that CRM trust and CRM commitment played a critical role in forming of purchase intention. Theoretical and practical Implications are discussed.

• Journal of Korea Multimedia Society
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• v.19 no.11
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• pp.1878-1890
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• 2016

Web 2.0 has features produced the content through the user of the participation and share. The content production activities have became active since social network service appear. The social bookmark, one of social network service, is service that lets users to store useful content and share bookmarked contents between personal users. Unlike Internet search engines such as Google and Naver, the content stored on social bookmark is searched based on tag keyword information and unnecessary information can be excluded. Social bookmark can make users access to selected content. However, quick access to content that users want is difficult job because of the user of the participation and share. Our paper suggests a method recommending search word to be able to access quickly to content. A method is suggested by using Collaborative Filtering and Jaccard similarity coefficient. The performance of suggested system is verified with experiments that compare by 'Delicious' and "Feeltering' with our system.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.12
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• pp.1154-1164
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• 2010

As an useful application in broadcasting services, the targeting service has been mainly studied to improve the service satisfaction and user usage in various media service environments based on user profile, preferences, and usage history. Targeting service is expanding its domain from broadcasting contents to interstitial contents and from fixed TV devices to mobile devices. Service data also include advertisement data, coupon, and information about media contents as well as simple broadcasting data. In this paper, the targeting data service is designed and implemented on articles, advertisement and broadcasting information on the basis of the user information. To adapt this to web-based media contents, information on user profile, preferences, and usage history is newly defined on the basis of the user metadata developed in TV-Anytime Forum and the user information defined in OpenSocial. The targeting data service is implemented to generate user preferences information and usage history pattern based on the similarity among user preference, contents information, and usage history. Based on performance evaluation, we prove that the proposed targeting data service is effectively applicable to web-based media contents as well as broadcasting service.

• Knowledge Management Research
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• v.18 no.3
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• pp.147-162
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• 2017

As social media started to work as important communication tools, social media users have tried to manage their image, identity, and impression through social media. Social media service providers have been interested in providing various functions effectively disclosing users' emotion, such as posting, commenting, and sharing content; on the other hand, relatively few efforts have been made to provide social media functions for information suppression. In this study, therefore, we attempt to examine the relationship between Facebook users' personality and impression management behaviors. Personal traits of users including public self-consciousness, positive self-expression, and honest self-expression were considered as independent variables. Impression management behaviors are composed of two variables, which are suppression and projection. The survey was conducted, targeting 230 Facebook users. The research findings show that public self-consciousness and positive self-expression are positively associated with information suppression while both positive and honest self-expression is positively associated with information projection.