• International Journal of Knowledge Content Development & Technology
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• 제7권4호
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• pp.27-50
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• 2017

The impact of social networking is varied from good to bad. Online activities have also been categorized into pros and cons of social networking, either as reported as hiding Internet activities among teenagers or killing loneliness among elderly. In terms of relationships, there have been argument over its closeness and quality of an online relationship in Internet settings. Looking at the contradiction in an innovative interaction between classic community communication and social media, there is an unknown scent of the future struggling and challenging both human communication and relationships in the presence of digital culture. This research uses Diffusion of Innovation to study the wide and continuous spread of digital culture in human communication; and, Media Dependency in learning and structuring the cognitive, affective and behavioral effects of social media on each person uses the media in different ways. This research will be using online survey to gain opinions from a social network site as an update of views and reflection of self-awareness to all levels of people. Social media like Facebook (FB) is perceived as a good tool of communication that it is able to bring closeness among the family members. The results show that social media like FB brings positive impact towards family members; it would help to build a better and harmonic society; and, relationships among family members and communication shall be improved and enhanced to the level of a united society.

• 농촌지도와개발
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• 제16권1호
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• pp.153-180
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• 2009

The previous researches about knowledge sharing were proceeded in terms of KMS (Knowledge Management System) in center. However, knowledge sharing is recently applied to Internet space, which is open to every users, as well as KMS, which is qualified for restricted people. For example, some portal sites, such as Naver, the most popular portal in Korea, have virtual spaces to share users' knowledges and it is common that many users use the spaces. Knowledge sharing online, compared with KMS, will be more advanced to promote intention for knowledge sharing because of the character of Internet space that is open to all users. Nevertheless, there are few researches about knowledge sharing in the Internet. Considering this situation, this study is attempted to figure out the factors to promote Internet knowledge sharing, based on social capital theory and self-expression concept. A survey of experienced Internet user and PLS (Partial Least Square) were utilized for analysis. The test of this study reveals that social capital and self-expression are significant factors to influence knowledge sharing intention, and that also personal innovation and self-efficacy are significantly related to the self-expression. However, personal innovation does not have significant impact on social capital. According to the result, self-expression, as well as trust and system itself, has significantly effect on knowledge sharing intention in order to promote knowledge sharing in the Internet.

• Asia pacific journal of information systems
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• 제30권1호
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• pp.143-165
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• 2020

The rapid growth of economic transactions generated by live streaming broadcasts ("LSB") has created opportunities for retailers to increase sales. However, little is known about what impact LSB celebrities have on customers and what causes LSB celebrities to become famous. This study aimed to fill this gap by studying the economics of LSBs. This study was conducted through a para-social relationship and attractiveness theory framework. Consequently, social and task attraction were assumed to be the antecedents of the para-social relationship that induced purchase intention. This study examined the impact of relationship rewards, self-disclosure, affective interactivity, informative interactivity, and the amount of information provided on purchase intentions through LSB. Celebrities can use the results of this study to enhance their appeal to fans and promote customers' purchase on e-commerce. This study contributed to the IS field by investigate the impact of para-social relationship on the online shopping context.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권6호
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• pp.1953-1972
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• 2022

The COVID-19 pandemic has resulted in a profound impact on large-scale gatherings throughout the world. Social distancing has become one of the most common measures to restrict the spread of the novel Coronavirus. Islamic pilgrimage attracts millions of pilgrims to Saudi Arabia annually. One of the mandatory rituals of pilgrimage is the symbolic stoning of the devil. Every pilgrim is required to perform this ritual within a specified time on three days of pilgrimage. This ritual is prone to congestion due to strict spatiotemporal requirements. We propose a pedestrian simulation model for implementing social distancing in the stoning ritual. An agent-based simulation is designed to analyze the impact of inter-queue and intra-queue spacing between adjacent pilgrims on the throughput and congestion during the stoning ritual. After analyzing several combinations of intra-queue and inter-queue spacings, we conclude that 25 queues with 1.5 meters of intra-queue spacing result in an optimal combination of throughput and congestion. The Ministry of Hajj in Saudi Arabia may benefit from these findings to manage and plan pilgrimage more effectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권3호
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• pp.1626-1638
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• 2019

Social Networking Sites (SNS) provide people with unique online social interaction environments where users can disclose their thoughts, feelings, and opinions to their personal contacts. Although previous studies have suggested that such activities produce positive effects on SNS user well-being, this study considered potential negative effects by investigating the relationship between SNS use and depression. In particular, This stydy examined how specific activities are related to different types of social comparison (upward/downward/horizontal) and how these different types of social comparison influence depressed moods among college students. The analysis of a survey of 245 Instagram users found that (1) looking at other people's status updates and commenting on other people's photos influences upward social comparison, (2) frequency of Instagram use predicts upward/downward/horizontal social comparison, and (3) upward social comparison was postively associated with depression, while downward social comparison was negatively associated with depression. Furthermore, the path anlaysis show that social comparison mediates the effect of Instagram use on depression. It suggests that Instagram use does not directly increase depression but it can lead to depression when social comparison on Instagram triggers depression.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권4호
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• pp.1643-1660
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• 2016

Connectivity and trust in social networks have been exploited to propose applications on top of these networks, including routing, Sybil defenses, and anonymous communication systems. In these networks, and for such applications, connectivity ensures good performance of applications while trust is assumed to always hold, so as collaboration and good behavior are always guaranteed. In this paper, we study the impact of differential behavior of users on performance in typical social network-enabled routing applications. We classify users into either collaborative or rational (probabilistically collaborative) and study the impact of this classification and the associated behavior of users on the performance of such applications, including random walk-based routing, shortest path based routing, breadth-first-search based routing, and Dijkstra routing. By experimenting with real-world social network traces, we make several interesting observations. First, we show that some of the existing social graphs have high routing costs, demonstrating poor structure that prevents their use in such applications. Second, we study the factors that make probabilistically collaborative nodes important for the performance of the routing protocol within the entire network and demonstrate that the importance of these nodes stems from their topological features rather than their percentage of all the nodes within the network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권12호
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• pp.3798-3814
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• 2022

Social recommendation algorithm can alleviate data sparsity and cold start problems in recommendation system by integrated social information. Among them, matrix-based decomposition algorithms are the most widely used and studied. Such algorithms use dot product operations to calculate the similarity between users and items, which ignores user's potential preferences, reduces algorithms' recommendation accuracy. This deficiency can be avoided by a metric learning-based social recommendation algorithm, which learns the distance between user embedding vectors and item embedding vectors instead of vector dot-product operations. However, previous works provide no theoretical explanation for its plausibility. Moreover, most works focus on the indirect impact of social friends on user's preferences, ignoring the direct impact on user's rating preferences, which is the influence of user rating preferences. To solve these problems, this study proposes a user bias drift social recommendation algorithm based on metric learning (BDML). The main work of this paper is as follows: (1) the process of introducing metric learning in the social recommendation scenario is introduced in the form of equations, and explained the reason why metric learning can replace the click operation; (2) a new user bias is constructed to simultaneously model the impact of social relationships on user's ratings preferences and user's preferences; Experimental results on two datasets show that the BDML algorithm proposed in this study has better recommendation accuracy compared with other comparison algorithms, and will be able to guarantee the recommendation effect in a more sparse dataset.

• International Journal of Internet, Broadcasting and Communication
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• 제9권3호
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• pp.59-69
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• 2017

The best 'hub' to communicate with the citizen is using social media to marketing the business. However, there has several issued and the most common issue that face in critical is a capital issue. This issue is always highlight because most of automatic sentiment detection tool for Facebook or any other social media price is expensive and they lack of technical skills in order to control the tool. Therefore, in directly they have some obstacle to get faster product's feedback from customers. Thus, the personal online retailing need to struggle to stay in market because they need to compete with successful online company such as G-market. Sentiment analysis also known as opinion mining. Aim of this research is develop the tool that allow user to automatic detect the sentiment comment on social media account. RAD model methodology is chosen since its have several phases could produce more activities and output. Soppy tool will be develop using Microsoft Visual. In order to generate an accurate sentiment detection, the functionality testing will be use to find the effectiveness of this Soppy tool. This proposed automated Soppy Tool would be able to provide a platform to measure the impact of the customer sentiment over the postings on their social media site. The results and findings from the impact measurement could then be use as a recommendation in the developing or reviewing to enhance the capability and the profit to their personal online retailing company.

• 한국콘텐츠학회논문지
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• 제21권11호
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• pp.294-306
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• 2021

브랜드 경쟁 시대에 기업은 소비자의 브랜드 신뢰도 및 충성도를 높이기 위해 많은 노력을 하고 있다. 기업의 사회적 책임이 기업의 브랜드 신뢰도 및 충성도를 높이는데 큰 역할을 하고 있다. 한편, 현재의 Covid-19 유행은 기업의 디지털 전환 속도를 가속화 했으며 소비자가 기업의 온라인 평가에 더 많은 관심을 기울이게 만들었다. 본 연구는 중국 소비자 시장을 기반으로 기업의 사회적 책임, 인터넷 입소문(e-WOM), 브랜드 신뢰를 통해 브랜드 충성도에 어떠한 영향을 미치는지에 대해 연구하였다. 이러한 연구목적을 확인하기 위해 본 논문에서는 중국과 한국에 있는 중국인 소비자를 대상으로 설문 조사를 실시하였다. 총 469개의 유효 설문이 사용되었고 수집된 데이터는 SPSS21.0를 활용해 실증 분석하였다. 연구 결과는 다음과 같이 요약된다. (1) 기업의 사회적 책임은 브랜드 신뢰에 긍정적인 영향을 미친다. (2) 기업의 사회적 책임은 브랜드 충성도에 긍정적인 영향을 미친다. (3) 브랜드 신뢰는 브랜드 충성도에 긍정적인 영향을 미친다. (4) 브랜드 신뢰와 인터넷 입소문은 기업의 사회적 책임과 브랜드 충성도의 사이에 긍정적인 매개효과가 나타낸다.

• International journal of advanced smart convergence
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• 제11권1호
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• pp.117-126
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• 2022

Corporate social responsibility (CSR) is the basic strategy for enterprises to obtain competitive advantages, and reflects the most basic value orientation and development concept of enterprises. The purpose of this study is to explore the relationship between corporate culture, innovation ability and core competitiveness of enterprises from the perspective of corporate social responsibility, and to establish a model and analyze the survey data of 32 agricultural science and technology enterprises in Tianjin by using SPSS23.0. As a result of the study, we found that corporate social responsibility (Ethical responsibility, Philanthropic responsibility) has a significant positive impact on corporate culture and innovation ability, corporate culture has a significant positive impact on innovation ability and corporate core competitiveness, and innovation ability has a significant positive impact on corporate core competitiveness. Therefore, it is suggested that agricultural science and technology enterprises should fulfill their social responsibilities, form a unique corporate culture, serve agriculture with science and technology, and constantly improve the ability of agricultural science and technology innovation, so as to enhance the core competitiveness of enterprises.