• Title/Summary/Keyword: social network service (SNS)

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An Investigation of Disability Awareness Between Occupational Therapists and None Therapists using SNS (SNS를 이용한 작업치료사와 일반인의 장애에 대한 인식 연구)

  • Hong, Deok-Gi;Bak, In-Hye;Moon, Jong-Hoon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.13 no.5
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    • pp.1125-1134
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    • 2018
  • The purpose of this study was comparing the disability awareness of occupational therapists and none therapists, and investigating the disability awareness according to the demographic characteristics of the respondents. The questionnaire was distributed through the online with a questionnaire based on social network service, and analyzed 62 responses of none therapists and 60 responses of occupational therapists. In results, disability awareness was not significantly different between occupational therapists and none therapists(p>.05). But, in subscale of disability awareness item 4 and 7, occupational therapists were significantly higher than none therapists(p<.05). In all respondents, disability awareness was more positive in males than females(p<.05). Also, there was no difference in disability awareness according to presence of disabled persons among family members or relatives(p>.05). However, All respondents who answered 'Yes' in the presence of disabled persons among family members or relatives in responders were significantly higher than those who answered 'No' in item 4(p<.05). There was no correlation between age and disability awareness(p>.05). The authors discussed suggestions in results of this study.

Facebook Users' Positive Self-Presentation toward Personal Characteristics (페이스북 이용자들의 긍정적인 자아노출과 자아속성)

  • Kim, Yoojung
    • The Journal of the Korea Contents Association
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    • v.17 no.9
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    • pp.21-31
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    • 2017
  • The purpose of study was to ascertain whether Facebook users present themselves positively on Facebook. Also this study examined whether factors of self-efficacy, narcissism, and public/private self-consciousness affected positive self-presentation. The subjects for the study included 197 users who have been using Facebook. The analysis of behavioral attributes such as self-display, competency display, exemplary behavior display, etc, did not yield statistically high values to support users' positive self-presentation on Facebook. The results showed that self-efficacy, narcissism, and public self-consciousness have statistically significant influence on positive self-presentation. The study found that private self-consciousness did not have statistically significant influence on positive self-representation.

Using Smart Phone and RFID Technology for making Ubiquitous Thema Park (스마트폰과 RFID를 이용한 u-테마파크 모델의 설계 및 구현)

  • Shin, Jae-myung;Kim, Doo-hyung;Ahn, Hongbum;Park, Sang-won;Hong, Jin-pyo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2010.11a
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    • pp.1478-1481
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    • 2010
  • 기존의 테마파크에 RFID를 이용하면 보다 편리하게 출입관리를 할 수 있고, 카드 한 장으로 테마파크 내에서 결제부터 부대시설과 서비스까지 이용할 수 있다. 이러한 모델은 이미 서브원 곤지암리조트 스키장과 캐리비언베이 워터파크 등 에서 도입하여 사용하고 있다[1][2]. 그러나 RFID를 이용한 유비쿼터스 모델들의 공통적인 단점은 RFID 카드 사용에 대한 피드백을 받을 수 없다는 것이다. 다시 말해서 RFID 카드에 대한 정보를 사용자는 모르기 때문에 자신이 RFID 카드로 무엇을 얼마나 결제했는지, 어떠한 서비스를 사용했는지 다시 확인할 수 없다는 문제점이 있다. 본 논문에서는 이러한 기존의 시스템에 스마트폰을 이용하여 사용자와 테마파크를 유기적으로 연결시켜줌으로써, 스마트폰을 통해 자신의 결제정보, 서비스 이용내역 등을 실시간으로 확인 가능할 수 있는 u-테마파크 모델을 제시한다. u-테마파크 모델을 이용하면 스마트폰을 통해 부대시설(놀이공원의 놀이기구, 스키장의 리프트 등)의 대기시간을 실시간으로 확인할 수 있고, RFID 카드를 소지한 일행의 위치를 찾을 수 있으며, 테마파크의 모든 이용객들과 정보를 교환할 수 있는 SNS(Social Network Service)등의 새로운 서비스를 제공할 수 있다. 테마파크 측에서는 실시간으로 취합되는 고객정보를 이용하여 이용률이 떨어지는 고객들의 특징을 파악해 해당 고객들에게 맞는 서비스를 제공하고 맞춤 마케팅을 하는 등의 체계적인 관리를 할 수 있어 다양한 마케팅과 새로운 서비스 제공이 가능하다는 이점이 있다.

Effect of Demographic Factors, Radiation Knowledge Level, Radiation Awareness on Radiation Benefit by Hierarchical Regression Analysis Model (위계적 회귀분석 모형에 의한 인구학적 요인, 방사선 지식수준, 방사선 인식도가 방사선 이익성에 미치는 영향)

  • Myeong-Hoon Ji;Youl-Hun Seoung
    • Journal of radiological science and technology
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    • v.46 no.5
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    • pp.435-444
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    • 2023
  • The purpose of this study was to analyze the factors that demographic factors, radiation knowledge level, and radiation awareness could be affecting the benefits of radiation. From July 2022 to July 2023, after receiving consent to participate by using the link of Naver through Social Network Service (SNS) for the general public, 312 people were surveyed by self-registration method without collecting personal information. The questionnaire consisted of a total of 25 questions following demographic factors (5 questions including age group by life cycle, sex, monthly household income, residence), radiation knowledge level (8 questions including basic physical, biological effects, radiation protection technology), radiation awareness (12 questions including risk, management, benefit). Independent sample T-test and ANOVA tests were performed for significant differences in the average radiation awareness between variables, and hierarchical regression was performed to identify influencing factors on radiation benefits. As a result, the benefit of radiation was significantly high among the radiation awareness, but the awareness of the danger of radiation was insufficient to the level of recognizing it as safe. Men had significantly higher awareness of radiation management and benefits than women, and the awareness of radiation management was significantly higher in the middle class with a monthly household income of 4.31 million won or more. The higher the knowledge level of radiation, the higher the awareness of the benefits of radiation. The factors that had a positive effect on radiation benefits were the high level of radiation knowledge and awareness of radiation management.

A Study on the Introductioin of Data Trusts System to Expand the Rights of Privacy Self-Determination (개인정보 자기결정권 확대를 위한 데이터 신탁제도 도입 방안 연구)

  • Jang, Keunjae;Lee, Seungyong
    • Journal of Intelligence and Information Systems
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    • v.28 no.1
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    • pp.29-43
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    • 2022
  • With the advent of the Internet and the development of mobile digital devices such as smartphones and tablet PCs, the communication service paradigm began to shift from existing voice services to data services. Recently, as social network services (SNS) are activated and 4th industrial revolution technologies centered on ICT (Information and Communication Technologies) such as Big Data, Blockchain, Cloud, and 5G/6G are rapidly developed, the amount of shared data type and the amount of data are increasing rapidly. As the transition to a digital society begins actively, the importance of using data information, as well as the economic and social values of personal information are becoming increasingly important. As a result, they are actively discussing policies to revitalize the data information industry around the world and ways to efficiently obtain, analyze, and utilize increasingly diverse and vast data, as well as to protect/guarantee the rights of information subjects (providers) in various fields such as society, culture, economy, and politics.. In this paper, in order to improve the self-determination right of personal information on data produced by information subjects, and further expand the use of safe data and the data economy, a differentiated data trusts system was considered and suggested. In addition, the components and data trusts procedures necessary to efficiently operate the data trusts system in Korea were considered, and the non-profit data trusts system and the for-profit data trusts system were considered as a way to flexibly operate the data trusts system. Furthermore, the legal items necessary for the implementation of the data trusts system were investigated and considered. In this paper, in order to propose a domestic data trusts system, cases related to existing data trusts systems such as the United States, Japan, and Korea were reviewed and analyzed. In addition, in order to prepare legislation necessary for the data trusts system, data-related laws in major countries and domestic legal and policy trends were reviewed to study the rights that conflict or overlap with existing laws, and differences were investigated and considered. The Data trusts system proposed in this paper is a reasonable system that is expected to recognize the asset value of data in the capitalist market economy system, to provide legitimate compensation for data produced by data subjects, and further to contribute greatly to the use of safe data and creation of a new service market.

Perception and Appraisal of Urban Park Users Using Text Mining of Google Maps Review - Cases of Seoul Forest, Boramae Park, Olympic Park - (구글맵리뷰 텍스트마이닝을 활용한 공원 이용자의 인식 및 평가 - 서울숲, 보라매공원, 올림픽공원을 대상으로 -)

  • Lee, Ju-Kyung;Son, Yong-Hoon
    • Journal of the Korean Institute of Landscape Architecture
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    • v.49 no.4
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    • pp.15-29
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    • 2021
  • The study aims to grasp the perception and appraisal of urban park users through text analysis. This study used Google review data provided by Google Maps. Google Maps Review is an online review platform that provides information evaluating locations through social media and provides an understanding of locations from the perspective of general reviewers and regional guides who are registered as members of Google Maps. The study determined if the Google Maps Reviews were useful for extracting meaningful information about the user perceptions and appraisals for parks management plans. The study chose three urban parks in Seoul, South Korea; Seoul Forest, Boramae Park, and Olympic Park. Review data for each of these three parks were collected via web crawling using Python. Through text analysis, the keywords and network structure characteristics for each park were analyzed. The text was analyzed, as were park ratings, and the analysis compared the reviews of residents and foreign tourists. The common keywords found in the review comments for the three parks were "walking", "bicycle", "rest" and "picnic" for activities, "family", "child" and "dogs" for accompanying types, and "playground" and "walking trail" for park facilities. Looking at the characteristics of each park, Seoul Forest shows many outdoor activities based on nature, while the lack of parking spaces and congestion on weekends negatively impacted users. Boramae Park has the appearance of a city park, with various facilities providing numerous activities, but reviewers often cited the park's complexity and the negative aspects in terms of dog walking groups. At Olympic Park, large-scale complex facilities and cultural events were frequently mentioned, emphasizing its entertainment functions. Google Maps Review can function as useful data to identify parks' overall users' experiences and general feelings. Compared to data from other social media sites, Google Maps Review's data provides ratings and understanding factors, including user satisfaction and dissatisfaction.

Structural features and Diffusion Patterns of Gartner Hype Cycle for Artificial Intelligence using Social Network analysis (인공지능 기술에 관한 가트너 하이프사이클의 네트워크 집단구조 특성 및 확산패턴에 관한 연구)

  • Shin, Sunah;Kang, Juyoung
    • Journal of Intelligence and Information Systems
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    • v.28 no.1
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    • pp.107-129
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    • 2022
  • It is important to preempt new technology because the technology competition is getting much tougher. Stakeholders conduct exploration activities continuously for new technology preoccupancy at the right time. Gartner's Hype Cycle has significant implications for stakeholders. The Hype Cycle is a expectation graph for new technologies which is combining the technology life cycle (S-curve) with the Hype Level. Stakeholders such as R&D investor, CTO(Chef of Technology Officer) and technical personnel are very interested in Gartner's Hype Cycle for new technologies. Because high expectation for new technologies can bring opportunities to maintain investment by securing the legitimacy of R&D investment. However, contrary to the high interest of the industry, the preceding researches faced with limitations aspect of empirical method and source data(news, academic papers, search traffic, patent etc.). In this study, we focused on two research questions. The first research question was 'Is there a difference in the characteristics of the network structure at each stage of the hype cycle?'. To confirm the first research question, the structural characteristics of each stage were confirmed through the component cohesion size. The second research question is 'Is there a pattern of diffusion at each stage of the hype cycle?'. This research question was to be solved through centralization index and network density. The centralization index is a concept of variance, and a higher centralization index means that a small number of nodes are centered in the network. Concentration of a small number of nodes means a star network structure. In the network structure, the star network structure is a centralized structure and shows better diffusion performance than a decentralized network (circle structure). Because the nodes which are the center of information transfer can judge useful information and deliver it to other nodes the fastest. So we confirmed the out-degree centralization index and in-degree centralization index for each stage. For this purpose, we confirmed the structural features of the community and the expectation diffusion patterns using Social Network Serice(SNS) data in 'Gartner Hype Cycle for Artificial Intelligence, 2021'. Twitter data for 30 technologies (excluding four technologies) listed in 'Gartner Hype Cycle for Artificial Intelligence, 2021' were analyzed. Analysis was performed using R program (4.1.1 ver) and Cyram Netminer. From October 31, 2021 to November 9, 2021, 6,766 tweets were searched through the Twitter API, and converting the relationship user's tweet(Source) and user's retweets (Target). As a result, 4,124 edgelists were analyzed. As a reult of the study, we confirmed the structural features and diffusion patterns through analyze the component cohesion size and degree centralization and density. Through this study, we confirmed that the groups of each stage increased number of components as time passed and the density decreased. Also 'Innovation Trigger' which is a group interested in new technologies as a early adopter in the innovation diffusion theory had high out-degree centralization index and the others had higher in-degree centralization index than out-degree. It can be inferred that 'Innovation Trigger' group has the biggest influence, and the diffusion will gradually slow down from the subsequent groups. In this study, network analysis was conducted using social network service data unlike methods of the precedent researches. This is significant in that it provided an idea to expand the method of analysis when analyzing Gartner's hype cycle in the future. In addition, the fact that the innovation diffusion theory was applied to the Gartner's hype cycle's stage in artificial intelligence can be evaluated positively because the Gartner hype cycle has been repeatedly discussed as a theoretical weakness. Also it is expected that this study will provide a new perspective on decision-making on technology investment to stakeholdes.

Clustering Method based on Genre Interest for Cold-Start Problem in Movie Recommendation (영화 추천 시스템의 초기 사용자 문제를 위한 장르 선호 기반의 클러스터링 기법)

  • You, Tithrottanak;Rosli, Ahmad Nurzid;Ha, Inay;Jo, Geun-Sik
    • Journal of Intelligence and Information Systems
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    • v.19 no.1
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    • pp.57-77
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    • 2013
  • Social media has become one of the most popular media in web and mobile application. In 2011, social networks and blogs are still the top destination of online users, according to a study from Nielsen Company. In their studies, nearly 4 in 5active users visit social network and blog. Social Networks and Blogs sites rule Americans' Internet time, accounting to 23 percent of time spent online. Facebook is the main social network that the U.S internet users spend time more than the other social network services such as Yahoo, Google, AOL Media Network, Twitter, Linked In and so on. In recent trend, most of the companies promote their products in the Facebook by creating the "Facebook Page" that refers to specific product. The "Like" option allows user to subscribed and received updates their interested on from the page. The film makers which produce a lot of films around the world also take part to market and promote their films by exploiting the advantages of using the "Facebook Page". In addition, a great number of streaming service providers allows users to subscribe their service to watch and enjoy movies and TV program. They can instantly watch movies and TV program over the internet to PCs, Macs and TVs. Netflix alone as the world's leading subscription service have more than 30 million streaming members in the United States, Latin America, the United Kingdom and the Nordics. As the matter of facts, a million of movies and TV program with different of genres are offered to the subscriber. In contrast, users need spend a lot time to find the right movies which are related to their interest genre. Recent years there are many researchers who have been propose a method to improve prediction the rating or preference that would give the most related items such as books, music or movies to the garget user or the group of users that have the same interest in the particular items. One of the most popular methods to build recommendation system is traditional Collaborative Filtering (CF). The method compute the similarity of the target user and other users, which then are cluster in the same interest on items according which items that users have been rated. The method then predicts other items from the same group of users to recommend to a group of users. Moreover, There are many items that need to study for suggesting to users such as books, music, movies, news, videos and so on. However, in this paper we only focus on movie as item to recommend to users. In addition, there are many challenges for CF task. Firstly, the "sparsity problem"; it occurs when user information preference is not enough. The recommendation accuracies result is lower compared to the neighbor who composed with a large amount of ratings. The second problem is "cold-start problem"; it occurs whenever new users or items are added into the system, which each has norating or a few rating. For instance, no personalized predictions can be made for a new user without any ratings on the record. In this research we propose a clustering method according to the users' genre interest extracted from social network service (SNS) and user's movies rating information system to solve the "cold-start problem." Our proposed method will clusters the target user together with the other users by combining the user genre interest and the rating information. It is important to realize a huge amount of interesting and useful user's information from Facebook Graph, we can extract information from the "Facebook Page" which "Like" by them. Moreover, we use the Internet Movie Database(IMDb) as the main dataset. The IMDbis online databases that consist of a large amount of information related to movies, TV programs and including actors. This dataset not only used to provide movie information in our Movie Rating Systems, but also as resources to provide movie genre information which extracted from the "Facebook Page". Formerly, the user must login with their Facebook account to login to the Movie Rating System, at the same time our system will collect the genre interest from the "Facebook Page". We conduct many experiments with other methods to see how our method performs and we also compare to the other methods. First, we compared our proposed method in the case of the normal recommendation to see how our system improves the recommendation result. Then we experiment method in case of cold-start problem. Our experiment show that our method is outperform than the other methods. In these two cases of our experimentation, we see that our proposed method produces better result in case both cases.

Semi-supervised learning for sentiment analysis in mass social media (대용량 소셜 미디어 감성분석을 위한 반감독 학습 기법)

  • Hong, Sola;Chung, Yeounoh;Lee, Jee-Hyong
    • Journal of the Korean Institute of Intelligent Systems
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    • v.24 no.5
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    • pp.482-488
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    • 2014
  • This paper aims to analyze user's emotion automatically by analyzing Twitter, a representative social network service (SNS). In order to create sentiment analysis models by using machine learning techniques, sentiment labels that represent positive/negative emotions are required. However it is very expensive to obtain sentiment labels of tweets. So, in this paper, we propose a sentiment analysis model by using self-training technique in order to utilize "data without sentiment labels" as well as "data with sentiment labels". Self-training technique is that labels of "data without sentiment labels" is determined by utilizing "data with sentiment labels", and then updates models using together with "data with sentiment labels" and newly labeled data. This technique improves the sentiment analysis performance gradually. However, it has a problem that misclassifications of unlabeled data in an early stage affect the model updating through the whole learning process because labels of unlabeled data never changes once those are determined. Thus, labels of "data without sentiment labels" needs to be carefully determined. In this paper, in order to get high performance using self-training technique, we propose 3 policies for updating "data with sentiment labels" and conduct a comparative analysis. The first policy is to select data of which confidence is higher than a given threshold among newly labeled data. The second policy is to choose the same number of the positive and negative data in the newly labeled data in order to avoid the imbalanced class learning problem. The third policy is to choose newly labeled data less than a given maximum number in order to avoid the updates of large amount of data at a time for gradual model updates. Experiments are conducted using Stanford data set and the data set is classified into positive and negative. As a result, the learned model has a high performance than the learned models by using "data with sentiment labels" only and the self-training with a regular model update policy.

An Analysis of the Roles of Experience in Information System Continuance (정보시스템의 지속적 사용에서 경험의 역할에 대한 분석)

  • Lee, Woong-Kyu
    • Asia pacific journal of information systems
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    • v.21 no.4
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    • pp.45-62
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    • 2011
  • The notion of information systems (IS) continuance has recently emerged as one of the most important research issues in the field of IS. A great deal of research has been conducted thus far on the basis of theories adapted from various disciplines including consumer behaviors and social psychology, in addition to theories regarding information technology (IT) acceptance. This previous body of knowledge provides a robust research framework that can already account for the determination of IS continuance; however, this research points to other, thus-far-unelucidated determinant factors such as habit, which were not included in traditional IT acceptance frameworks, and also re-emphasizes the importance of emotion-related constructs such as satisfaction in addition to conscious intention with rational beliefs such as usefulness. Experiences should also be considered one of the most important factors determining the characteristics of information system (IS) continuance and the features distinct from those determining IS acceptance, because more experienced users may have more opportunities for IS use, which would allow them more frequent use than would be available to less experienced or non-experienced users. Interestingly, experience has dual features that may contradictorily influence IS use. On one hand, attitudes predicated on direct experience have been shown to predict behavior better than attitudes from indirect experience or without experience; as more information is available, direct experience may render IS use a more salient behavior, and may also make IS use more accessible via memory. Therefore, experience may serve to intensify the relationship between IS use and conscious intention with evaluations, On the other hand, experience may culminate in the formation of habits: greater experience may also imply more frequent performance of the behavior, which may lead to the formation of habits, Hence, like experience, users' activation of an IS may be more dependent on habit-that is, unconscious automatic use without deliberation regarding the IS-and less dependent on conscious intentions, Furthermore, experiences can provide basic information necessary for satisfaction with the use of a specific IS, thus spurring the formation of both conscious intentions and unconscious habits, Whereas IT adoption Is a one-time decision, IS continuance may be a series of users' decisions and evaluations based on satisfaction with IS use. Moreover. habits also cannot be formed without satisfaction, even when a behavior is carried out repeatedly. Thus, experiences also play a critical role in satisfaction, as satisfaction is the consequence of direct experiences of actual behaviors. In particular, emotional experiences such as enjoyment can become as influential on IS use as are utilitarian experiences such as usefulness; this is especially true in light of the modern increase in membership-based hedonic systems - including online games, web-based social network services (SNS), blogs, and portals-all of which attempt to provide users with self-fulfilling value. Therefore, in order to understand more clearly the role of experiences in IS continuance, analysis must be conducted under a research framework that includes intentions, habits, and satisfaction, as experience may not only have duration-based moderating effects on the relationship between both intention and habit and the activation of IS use, but may also have content-based positive effects on satisfaction. This is consistent with the basic assumptions regarding the determining factors in IS continuance as suggested by Oritz de Guinea and Markus: consciousness, emotion, and habit. The principal objective of this study was to explore and assess the effects of experiences in IS continuance, with special consideration given to conscious intentions and unconscious habits, as well as satisfaction. IN service of this goal, along with a review of the relevant literature regarding the effects of experiences and habit on continuous IS use, this study suggested a research model that represents the roles of experience: its moderating role in the relationships of IS continuance with both conscious intention and unconscious habit, and its antecedent role in the development of satisfaction. For the validation of this research model. Korean university student users of 'Cyworld', one of the most influential social network services in South Korea, were surveyed, and the data were analyzed via partial least square (PLS) analysis to assess the implications of this study. In result most hypotheses in our research model were statistically supported with the exception of one. Although one hypothesis was not supported, the study's findings provide us with some important implications. First the role of experience in IS continuance differs from its role in IS acceptance. Second, the use of IS was explained by the dynamic balance between habit and intention. Third, the importance of satisfaction was confirmed from the perspective of IS continuance with experience.