• 지식경영연구
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• 제16권3호
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• pp.81-102
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• 2015

With the rapid development of digital media, there has been a huge change in a way of communication, a process of information diffusion and a role of traditional media. Not like mass media, social media enables users to generate and tap into the opinions of a larger world. From that reason, social media is impacting marketing strategies. However, still social media marketing researches just focus on case study, analysis of users motivation or analysis of power user's usage pattern. Word-of-mouth has always been important especially in marketing area. In social media, word-of-mouth depends on each user that's why this research focuses on individual user's activity in SNS. I defined 4 factors (produce, diffusion, network size, activity of network size enlarge) that are effect on activity and verified hypothesis by multiple regression analysis, hierarchical regression analysis and moderated multiple regression.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권5호
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• pp.2484-2498
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• 2017

Various types of social media make the people share their personal experience in different ways. In some social networking sites. Some users post their reviews, some users can support these reviews with comments, and some users just rate the reviews as kind of support or not. Unfortunately, there is rare explicit negative comments towards other reviews. This means if there is a link between two users, it must be positive link. Apparently, the negative link is invisible in these social network. Or in other word, the negative links are redundant to positive links. In this work, we first discuss the feature extraction from social media data and propose new method to compute the distance between each pair of comments or reviews on social media. Then we investigate whether we can predict negative links via regression analysis when only positive links are manifested from social media data. In particular, we provide a principled way to mathematically incorporate multi-facet data in a novel framework, Constructing Negative Links, CsNL to predict negative links for discovering the hidden information. Additionally, we investigate the ways of solution to general negative link predication problems with CsNL and its extension. Experiments are performed on real-world data and results show that negative links is predictable with multi-facet of social media data by the proposed framework CsNL. Essentially, high prediction accuracy suggests that negative links are redundant to positive links. Further experiments are performed to evaluate coefficients on different kernels. The results show that user generated content dominates the prediction performance of CsNL.

• 한국컴퓨터정보학회논문지
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• 제23권4호
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• pp.25-31
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• 2018

In recent years the privacy issue on social media is often being discussed. The purpose of this study is to explore the relationships among user gender, user group according to user activity level (highly active vs less active) and self-disclosure in social media. We collected a total of 180 million tweets issued by 13 million twitter users for 12 months and investigated attributes of tweet (user's profile, profile image, description, geographic information, URL) which are related to self-disclosure and boundary impermeability. The results show there are significant (p<0.001) interactions between user gender, user group and each attribute of tweet that are related to self-disclosure and show that the patterns of self-disclosure are different across attributes. The results also show that the mean self-disclosure scores and boundary impermeability of top 10% highly active users are significantly higher than other less active users for all genders.

• International Journal of Computer Science & Network Security
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• 제21권12spc호
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• pp.579-585
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• 2021

This study aims to provide an in-depth description of the practices of social media users in the Kingdom of Saudi Arabia (KSA)-specifically the users of Facebook and Snapchat-and the reasons for these practices, the decisions made, and the people involved. Qualitative methods were used to collect data in two rounds from 53 participants. The data analysis shows a clear preference for Snapchat over Facebook among the participants, as shown in their using the application many times daily and in the creation and use of new words derived from the application's name. On the other hand, one of the main reasons mentioned by the participants for not preferring Facebook was the unclear policy of security and privacy used in the application. This reason is important for all social media users, but, in particular, it is crucial for female users, as shown in the data. This is important for the designers and policymakers of the social media applications to understand and consider, as it would help them improve the current applications and create new ones.

• Asian Journal for Public Opinion Research
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• 제10권1호
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• pp.51-73
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• 2022

This study investigated 3.50 million Facebook reactions collected from 9,429 Bangladeshi news items about rape shared on social media from 2016 to 2021. The primary aim of this study was to understand users' different reaction patterns based on the five major Facebook reactions (i.e., love, haha, wow, sad, and angry). Based on the theories of emotion, we quantitatively answer one research question: How do social media users react to rape with the five major Facebook reactions? The results suggest that users are more likely to express disdain toward rape and sympathy toward the victims using Facebook reactions by using the angry button, along with the sad button. In rape news, both reactions are consistent and maintain a strong positive correlation, meaning they increase and decrease together. Although many users tend to mock and laugh at rape incidents and the victims, trend lines suggest that such expressions may not be consistent with time. Despite contextual relevance, we presume that in socially and morally unacceptable events like rape and war, the valences of reactions alter to some extent: angry and sad usually become positive, while love, wow, and haha become negative. Some strengths and limitations of the study are discussed as well.

• Journal of Contemporary Eastern Asia
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• 제20권2호
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• pp.108-128
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• 2021

Research on the news coverage of North Korea has been paying less attention to social media platforms than to legacy media. An increasing number of social media users post, retweet, share, interpret, and set agendas on North Korea. The accessibility of international users and North Korea's publicity purposes make social media a venue for expression, news diversity, and framing about the nation. This study examined the sentiment of Twitter posts on North Korea from a framing perspective and the relationship between network strengths and sentiment from a social network perspective. Data were collected using two tools: Jupyter Notebook with Python 3.6 for preliminary analysis and NodeXL for main analysis. A total of 11,957 tweets, 10,000 of which were collected using Python and 1,957 tweets using NodeXL, about North Korea between June 20-21, 2020 were collected. Results demonstrated that there was more negative sentiment than positive sentiment about North Korea in the sampled Twitter posts. Some users belonging to small network sizes reached out to others on Twitter to build networks and spread positive information about North Korea. Influential users tended to be impartial to sentiment about North Korea, while some Twitter users with a small network exhibited high percentages of positive words about North Korea. Overall, marginalized populations with network bonding were more likely to express positive sentiment about North Korea than were influencers at the center of networks.

• Asia pacific journal of information systems
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• 제34권1호
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• pp.91-113
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• 2024

In the wake of the COVID-19 pandemic, unsubstantiated information concerning vaccines and the coronavirus has proliferated on various social media platforms. Consequently, we have considered viable actions to mitigate the impact of such unverified content, enabling individuals to use social media platforms more effectively and minimize any ensuing confusion. Recent measures in this area have included YouTube's practice of labeling vaccine or corona videos as authoritative when emanating from reputable organizations and Twitter's practice of flagging vaccine-related content as potentially misleading or taken out of context. This study seeks to explore how such contrasting labeling practices influence users' believability and engagement differentially, while also examining the moderating impact of regulatory focus. The results indicate that authoritative labeling positively influenced users' believability and engagement, whereas misleading labeling adversely affected users' believability and engagement. Additionally, our findings revealed that authoritative labeling has a stronger impact on promotion-focused individuals, while misleading labeling has a more pronounced effect on prevention-focused individuals. Our findings offer insights into how social media platforms can design and present information to their users, taking into account their regulatory focus.

• 지식경영연구
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• 제18권4호
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• pp.137-157
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• 2017

With the rapid growth of the internet, Social Network Services (SNSs) have played an important role. As the use of SNSs increases, users experience a sense of responsibility to respond to other people's messages or requests, and consequently experience an social overload, feeling too much social support for other users. In this study, we examined the effects of social overload on loneliness and SNS discontinuous usage intention. To verify the research model, data were collected from 83 SNS users and analyzed using SmartPLS, a structural equation modeling tool. The results of this study showed that the communal orientation and the degree of use of SNS influenced the social overload, and the social overload had a significant effect on loneliness and SNS discontinuous usage intention. The findings of this study are expected to help understand the social overload and loneliness in the use of SNS, and may also provide a strategic direction for SNS service providers.

• 인터넷정보학회논문지
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• 제18권1호
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• pp.89-103
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• 2017

이 연구는 정부의 위기 상황에서, 정부 운용 소셜 미디어의 매체 환경적 특성에 따라 이용자의 참여가 얼마나 능동적인지, 메시지 확산 유형에 어떤 영향을 미치는지 살펴보았다. 소셜 미디어 환경을 인간 상호작용성과 매체 상호작용성을 기준으로 유형화했고, 이용자의 능동성은 좋아요, 공감 같은 감정을 표현하는지, 댓글까지 쓰는지를 기준으로 능동성 정도를 측정했다. 소셜 미디어에 올라온 댓글에 대해서는 네트워크 분석을 통해 유형화했다. 분석 결과 정보제공 참여형과 관계지향적 참여형의 경우, 이용자의 능동적 참여가 높게 나타났고, 정보 제공형과 제한적 플랫폼에서 능동적 참여가 낮았다. 메시지 확산 유형을 분석한 결과 제한적 플랫폼에서 합리적 의견 제한형이 나타났고, 나머지 소셜 미디어 환경에서는 감정적 의견 확산형과 감정적 의견 제한형이 형성됐다. 메르스 사태와 같은 위기 상황에서 정부는 소셜 미디어의 매체 환경적 특성에 적합한 메시지를 제공하지 못하는 것으로 나타났고, 이러한 매체 환경은 이용자의 참여와 댓글 형성에 영향을 미친 것을 알 수 있었다. 정부는 이용자와의 상호작용성을 증가시켜 이용자 친화적인 소셜 미디어 환경을 만들고, 위기 상황에서 이용자와 소통하는 노력을 해야 할 것이다.

• Journal of Contemporary Eastern Asia
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• 제12권2호
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• pp.49-59
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• 2013

Social media such as Twitter and Facebook have become popular. In the age of social media, many people have become more active online. For example, about half of all global active Internet users are on Facebook (Perry 2012). Personal branding is a very important strategy to build on an individual's strengths, and this kind of branding is expected to contribute to self-actualization. Therefore, the presence of mentors who advise users to discover their own strong points for self-actualization is necessary. In this paper, we propose a personal branding support service, Mentors, which connects mentors and mentees. The core concept is: "Everyone has the face of both a mentor and mentee." The key function is sharing stages of self-analysis in human life design: Determining value, creating a mission, and forming a strategy. From this function, a good match between a mentor and mentee can be found. The program aims to improve human life by understanding the client's strengths and using social media effectively. Future work includes launching Mentors and evaluating its service.