• International Journal of Contents
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• 제14권4호
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• pp.51-56
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• 2018

This study was conducted to explore the relationship between personality characteristics and mood in the selection of media content. Using meta-analysis, this study analyzed past studies regarding media content selection in television program. The results of this research showed that the preference of a given media content would depend on the viewer's mood, personality characteristics and the interaction between personality characteristics and mood states. The secondary data of television programs supported the association.

• 한국의류학회지
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• 제35권8호
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• pp.877-889
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• 2011

This study investigates the effects of social media's fashion advertisements. A survey was taken among men and women in their twenties who had experiences with fashion brand social media. A total of 270 questionnaires were used in this analysis. The results are as follows: First, the factors of content and pursuit of information had positive (+) impacts on advertisement attitude for both men and women in the fashion brand communities. Only the pursuit of information had positive (+) effects on men's brand attitude; however, economy, self-satisfaction, and the pursuit of information influenced women's brand attitude and purchase intention. Secondly, in fashion brand video UCCs, pursuit of information and the formation of relationships had positive (+) impacts on men and women, respectively. The formation of relationships had positive (+) impacts on men's brand attitude; however, the formation of relationships and the pursuit of information influenced women's brand attitude. The pursuit of information and formation of relationships had a positive (+) influences on men's and women's purchase intention, respectively. Men had differences in the pursuit of information and advertisement attitude in the two types of fashion brand communities and video UCCs; however, women had differences in economy and self-satisfaction, advertisement attitude, and brand attitude in the two types. The study results provide basic data by examining men and women in their twenties who have easy access to the Internet for advertisement attitude, brand attitude, and purchase intention in social media as an online fashion advertising media as well as useful information for establishing marketing strategies.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2009년도 학술대회
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• pp.301-309
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• 2009

This study focuses on event-driven social media (EDSM), which supports the production of unique cultural items of small groups by satisfying the conflicting desires of distinctiveness and assimilation that small groups possess. EDSM is a system which promotes the production of idioculture through small group interaction by using an actual event in which people participate in small groups. By setting up an EDSM system in a university festival in which 10,000 to 15,000 people gather in small groups, idioculture production was tested for approximately eight hours and a half. Interaction records gathered from the test, as well as focus group interview data garnered soon after were used to analyze usage patterns of EDSM, types of idiocultures produced, and resulting factors of user experience. Through this, considerations upon designing future EDSM were proposed.

• Journal of information and communication convergence engineering
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• 제15권3호
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• pp.170-174
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• 2017

Nowadays, people share and discuss scientific papers on social media such as the Web 2.0, big data, online forums, blogs, Twitter, Facebook and scholar community, etc. In addition to a variety of metrics such as numbers of citation, download, recommendation, etc., paper review text is also one of the effective resources for the study of scientific impact. The social media tools improve the research process: recording a series online scholarly behaviors. This paper aims to research the huge amount of paper reviews which have generated in the social media platforms to explore the implicit information about research papers. We implemented and shown the result of text mining on review texts using R language. And we found that Zika virus was the research hotspot and association research methods were widely used in 2016. We also mined the news review about one paper and derived the public opinion.

• Nuclear Engineering and Technology
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• 제55권6호
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• pp.2026-2033
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• 2023

Due to Thailand's nuclear energy public acceptance problem, the understanding of nuclear energy public perception was the key factor affecting to re-consideration of the nuclear energy program. Thailand Institute of Nuclear Technology and its alliances together developed the classification model for the nuclear energy public perception from the big data comments on social media using Facebook using deep transfer learning. The objective was to insight into the Thailand nuclear energy public perception on Facebook social media platform using sentiment analysis. The supervised learning was used to generate up-to-date classification model with more than 80% accuracy to classify the public perception on nuclear power plant news on Facebook from 2009 to 2022. The majority of neutral sentiments (80%) represented the opportunity for Thailand to convince people to receive a better nuclear perception. Negative sentiments (14%) showed support for other alternative energies due to nuclear accident concerns while positive sentiments (6%) expressed support for innovative nuclear technologies.

• International Journal of Computer Science & Network Security
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• 제24권7호
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• pp.186-194
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• 2024

This study aims to investigate the technological-organizational-environmental (TOE) factor of influencing small and medium-sized enterprises (SMEs') social media (SM) adoption in developing countries. This study used a closed-ended questionnaire to collect data from randomly selected respondents (owners, executives, and managers) from SMEs operating in Pakistan. SMART PLS version 3.2.8 was used for path analysis of 423 responses. The research findings include the direct influence of TOE factors on SMEs SM adoption and SMEs performance. Furthers, this paper also has implications for practitioners and scholars interested in exploring the SM adoption and usage in SMEs.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2015년도 제52차 하계학술대회논문집 23권2호
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• pp.93-94
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• 2015

본 논문에서는 학교 교육환경에서 청소년들에게 발생 할 수 있는소 셜미디어의 역기능을 빅 데이터 처리를 통하여 분석 할 수 있는 방법을 제시하고, 특히 악성 댓글을 위주로 한 청소년들 간의 소셜미디어를 중심으로 빅 데이터의 마이닝 기술을 활용하여 대표적인 청소년 문제의 확산을 방지 할 수 있는 시스템 제안한다.

• 한국안전학회지
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• 제32권3호
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• pp.83-89
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• 2017

A new technology has provided the nation, industry, society, and people with innovative and useful functions. National economy and society has been improved through this technology innovation. Despite the benefit of technology innovation, however, since technology society was sufficiently mature, the unintended side effect and negative impact of new technology on society and human beings has been highlighted. Thus, it is important to investigate a risk of new technology for the future society. Recently, the risks of the new technology are being suggested through a large amount of social data such as news articles and report contents. These data can be used as effective sources for quantitatively and systematically forecasting social risks of new technology. In this respect, this paper aims to propose a data-driven process for forecasting and assessing social risks of future new technology using the text mining, 4M(Man, Machine, Media, and Management) framework, and analytic hierarchy process (AHP). First, social risk factors are forecasted based on social risk keywords extracted by the text mining of documents containing social risk information of new technology. Second, the social risk keywords are classified into the 4M causes to identify the degree of risk causes. Finally, the AHP is applied to assess impact of social risk factors and 4M causes based on social risk keywords. The proposed approach is helpful for technology engineers, safety managers, and policy makers to consider social risks of new technology and their impact.

• Journal of Information Technology Applications and Management
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• 제22권2호
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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.

• 지식경영연구
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• 제15권4호
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• pp.189-206
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• 2014

Knowledge management is considered an important factor for competitive advantage and sustainability for firms. As many knowledge management systems failed to achieve the desired results, enterprise social media (ESM) has received considerable attention as an alternative solution for knowledge sharing within a firm. This paper attempts to investigate the influence of various aspects of ESM on knowledge sharing. While previous literature mainly focused on structural aspects of ESM, this study focuses on social psychological aspects, such as social connectedness, social awareness, and social presence, along with reputational aspects (such as self-presentation). Further, in order to clarify knowledge sharing behavior, this study classifies knowledge sharing behavior into two categories, knowledge contribution and knowledge acquisition. The data used in this study was collected from 179 individuals who have experience in their own ESM. The results show that both social connectedness and self-presentation positively influence the two types of knowledge sharing behavior, i.e., acquisition and contribution. Meanwhile, social awareness turns out to be a significant determinant of knowledge contribution only. Contrary to our expectations, however, social presence does not significantly influence knowledge sharing behavior.