• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.283-290
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• 2023

This study investigates the influential factors on online word-of-mouth (eWOM) intentions towards educational tourist destinations, primarily focusing on Korean universities and Chinese tourists. It reveals a positive correlation between eWOM intentions and the desire to enroll in these institutions. The significance of eWOM for attracting Chinese students elucidates the importance of establishing a strong brand image and ensuring high levels of tourist satisfaction. Moreover, social media users who travel for education purposes were found to emphasize self-image consistency and conspicuous self-expression. This research underscores the utility of leveraging social media to enhance the perception of educational tourist attractions, promoting these destinations, and stimulating eWOM, thereby enriching the understanding of the strategic use of social media in international student recruitment.

• Korean journal of communication and information
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• v.61
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• pp.134-158
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• 2013

The public trades information through social media during crises. The use of social media during crises has been increased steadily. However, there are few studies done on the effects of social media use on crisis perception. The goal of this study is to examine how social media affect an organization's ability to manage crises. The study specifically tries to investigate how media types, organization-public relationships, and image restoration strategies affect the public's perception of crises. An experiment was conducted to test research questions by presenting crisis scenarios and observing how newspapers and the social media Twitter affected the crisis. According to a three-way ANOVA test, the type of media and image restoration strategies had an interaction effect on the public's perception of crises. Also, the type of media, organization-public relationship, and image restoration strategies had a three way effect toward the acceptance of crisis communication strategies. As a result, it can be said that the public's perception and acceptances of crisis communication were different depending on the type of media used. The effectiveness of social media was proved, and it was seen that to be able to effectively use social media, each organization must have different strategies depending on their needs.

• Journal of the Korean Society for information Management
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• v.33 no.2
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• pp.135-156
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• 2016

Recently, as the importance of user-oriented archives management is becoming increasingly, government archives try to serve interactive services using social network service (SNS) beyond one-way approaches. This study aims to analyze usage of government archives service in social media and examine users' interestedness. We especially select "National Archives of Korea" and "Presidential Archives" as target government archives and collect tweets from 2010 to 15th April 2016. Our study adopts informetric approaches and social media analysis including buzz analysis, time series analysis. We differentiate between the tweet collection posted by government archives themselves and the other collection generated by general users. Furthermore we conduct correlation analysis of tweet and social issues and propose application plan for government archives services in social media environment.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.4
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• pp.199-209
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• 2019

The importance of business strategy for successful social media engagement has quickly increased as more businesses engage in social media. The importance is even greater for startup companies because startup companies are genuinely new to business, and they need to increase their presence in the market, and quickly access future customers. The objective of this paper lies in exploring key indicators of social media engagements by selected startup companies. The key indicators include two aspects of social media usages by the companies: i) overall social media activities, and ii) properties of network structure of the information flow platform provided by social media service. To better assess and evaluate the key indicators of social media usages by startup companies, the indicators will be compared with those of selected large established companies. Twitter is selected as a social media service for the analysis of this paper, and using Twitter REST API, data regarding the key indicators of overall Twitter activities and the Twitter follower-network of each company in the sample are collected. Then, the data are analyzed using social network analysis and hierarchical clustering analysis to examine the characteristics of the follower-network structures and to compare the characteristics between startup companies and established companies. The results show that most indicators are significantly different across startup companies and established companies. One key interesting finding is that the startup companies have proportionally more influencers in their follower-networks than the established companies have. Another interesting finding is that the follower-networks of startup companies in the sample have higher modularity and higher transitivity, suggesting that the startup companies tend to have a proportionally larger number of communities of users in their follower-networks, and the users in the networks are more tightly connected and cohesive internally. The key business implication for the future social media engagement efforts by startup companies in general is that startup companies may need to focus on getting more attention from influencers and promoting more cohesive communities in their follower-networks to appreciate the potential benefits of social media in the early stage of business of startup companies.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.5
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• pp.169-175
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• 2023

This paper analyzes museum-related big data using museums and gamification using social media big data, identifies and compares the perceptions of visitors mentioned in social media, and presents ways to use gamification. Based on the collected data, this paper aims to provide data by comparing and analyzing the perception of visitors to the museum and visitors to the museum using gamification. This paper investigates the perception of visitors through social media analysis using TEXTOM, a social media analysis tool, to identify differences in perception. As a result of the analysis, it was found that compared to museums that were previously viewed in the form of exhibitions, they felt fun and interest in visiting museums using geikipication. In addition, based on the analysis results of keywords and related keywords, the perception, motivation, and type of viewing of the museum of the National Museum of Korea and the Independence Hall of Korea were confirmed. In addition, it can be seen that the sense of achievement of visitors who visited the museum using gamification is higher than that of the existing museum. It is believed that by developing and activating game-related content in future museum visits, many visitors will be able to increase their interest in the museum and feel fun and interested. The results of the study are believed to be meaningful as basic data to grasp the overall perception of visitors to the museum, and based on this, it is expected that visitors will be able to see and experience the museum in various ways.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.05a
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• pp.519-522
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• 2020

1989년에 WWW(World Wide Web)이 도입 되면서 세계적으로 인터넷의 보급이 시작되었다. 정보화 시대라고 알려진 3차 산업혁명 이후로 대량의 정보들이 소셜 미디어를 통하여 생산되었다. 소셜미디어는 2007년에 인터넷 사용자들 중 56%의 이용률을 보였지만 2008년 2분기에는 75%의 이용률로 증가함에 따라 대부분의 사용자들이 많이 사용하며 의존하게 되었다. 또한 소셜 미디어를 통해 발생 되는 데이터들을 이용하여 기업들은 이윤 창출을 할 수 있다. 하지만 이러한 소셜 미디어는 악의적인 목적을 통해 주가 조작, 정치적 선동 등을 할 수 있는 가짜 뉴스와 허위 정보들을 생성할 수 있으며 이에 따라 대책이 시급하다. 또한 가짜 뉴스는 사람이 글을 작성할 수도 있지만 최근 인공지능 기술의 발달에 따라 프로그램을 통해 자동적으로 생성 될 수도 있다. 본 논문에서는 이와 같은 실제 뉴스와 인공지능을 기반으로 한 뉴스를 분석한다. Kaggle에서 실제 뉴스 데이터를 수집하여 헤드라인을 OpenAI의 GPT-2 언어 모델을 통해 뉴럴 가짜 뉴스를 생성 하였다. 파이썬의 NLTK 모듈을 이용하여 전처리를 진행하였고 t-검정과 박스 플롯을 활용하여 분석을 진행하였다. 분석된 주요 속성들을 의사결정트리를 통해 모델 검증을 하였고 k-fold 교차검증을 통해 분류 모델을 평가하였다. 결과로 전체 분류 정확도 평균 89%의 성능을 보여주었다.

• Journal of Korean Library and Information Science Society
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• v.53 no.3
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• pp.263-285
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• 2022

This study presented the factor analysis on constructing the new factors affecting the middle school students' online learning behaviors from the questionnaires employed among middle school students. A total of 204 students participated and the data were collected in South Korea. The sample of middle school ninth-grade students was selected and used through purposive sampling. Findings from the factor analysis provided evidence for the eight-factor solution for the 35-items accounting for 66.15% of the shared variance. A wide range of factors has been considered to identify students' online learning behaviors. The appropriate experience and use of e-learning in the middle school period is also important as it will be a critical stepstone for future education. This research provides information that has been taken into account for advancing online learning to enhance the quality of e-learning systems for middle school students. The study results provided eight new factors affecting the middle school students' online learning behaviors; that is 1) communication using social media as a learning tool, 2) intention to share information using ICT, 3) addiction of technology, 4) adoption of technology, 5) seeking information using ICT, 6) use of social media learning, 7) information search using ICT, and 8) immersion of technology. This study confirmed that middle school students prefer communication using social media as a learning tool, and value intention to share information using ICT for the most part. The data obtained based on factor analysis can highlight the online learning behaviors towards a mixture of social media learning and ICT to ensure a new educational platform for the future of e-learning. This research expects to be useful for both middle schools of online learning to better understand students' online learning behaviors and design online learning environments and information professionals to better assist students who particularly need digital literacy.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.3
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• pp.861-870
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• 2017

In this paper, we propose the roles of social robots in educational environments. This proposal becomes an extension of R-learning. The purpose of social robots is the communication and interaction with human. Social robots have two roles. One is similar to the role of educational service robot and the other is communication role with people in education environments. We make an scenario to explain how to operate the roles of social robots using robot jibo SDK. The scenario was designed for mild interaction with the user in the educational environment. And it was made using jibo animation part to control the external reaction of jibo and behaviors part to control the internal reaction in jibo SDK. Social robots collect data effectively, based on grafting technologies and interaction with people in educational environments. Concludingly, various data collected by social robots contribute to solving problems, developing and establishing of educational environments.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.6
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• pp.42-57
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• 2022

This study aims to create a basic model for classifying the activity photos that urban park users shared on social media using Deep Learning through Artificial Intelligence. Regarding the social media data, photos related to urban parks were collected through a Naver search, were collected, and used for the classification model. Based on the indicators of Naturalness, Potential Attraction, and Activity, which can be used to evaluate the characteristics of urban parks, 21 classification categories were created. Urban park photos shared on Naver were collected by category, and annotated datasets were created. A custom CNN model and a transfer learning model utilizing a CNN pre-trained on the collected photo datasets were designed and subsequently analyzed. As a result of the study, the Xception transfer learning model, which demonstrated the best performance, was selected as the urban park user activity image classification model and evaluated through several evaluation indicators. This study is meaningful in that it has built AI as an index that can evaluate the characteristics of urban parks by using user-shared photos on social media. The classification model using Deep Learning mitigates the limitations of manual classification, and it can efficiently classify large amounts of urban park photos. So, it can be said to be a useful method that can be used for the monitoring and management of city parks in the future.

• Journal of Korea Multimedia Society
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• v.13 no.8
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• pp.1245-1255
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• 2010

In current Web 2.0 environment, one of the most core technology is social bookmarking which users put tags and bookmarks to their interesting Web pages. The main purpose of social bookmarking is an effective information service by use of retrieval, grouping and share based on user's bookmark information and tagging result of their interesting Web pages. But, current social bookmarking system uses the number of bookmarks and tag information separately in information retrieval, where the number of bookmarks stand for user's degree of interest on Web contents, information retrieval, and classification serve the purpose of tag information. Because of above reason, social bookmarking system does not utilize effectively the bookmark information and tagging result. This paper proposes a Web contents ranking algorithm combining bookmarks and tag information, based on preceding research on associative tag extraction by tag clustering. Moreover, we conduct a performance evaluation comparing with existing retrieval methodology for efficiency analysis of our proposed algorithm. As the result, social bookmarking system utilizing bookmark with tag, key point of our research, deduces a effective retrieval results compare with existing systems.