• Journal of Contemporary Eastern Asia
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• v.20 no.2
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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.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.445-454
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• 2021

Leader and leadership are one of the important aspects in the life of a country. This study aims to predict the intention of young voters to vote for state leader elections by expanding the theory of planned behavior to the Indonesian context. Apart from the importance of the presidential election, research rarely uses the theory of planned behavior, and to the best of researchers' knowledge, there are no studies that have applied the theory of planned behavior to predict the intention to vote for the president. Therefore, this study is an attempt to fill that gap. Two hundred questionnaires were distributed using non-probability purposive sampling. Data analysis was carried out using the structural equation modeling (SEM) approach. The results showed that attitude and behavior control were positively related to voters' intention to elect presidential candidates. Furthermore, information from social media also has a positive relationship with the attitude of choosing presidential candidates. However, the results also show that subjective norms do not have a significant relationship with voters' intention. This study contributes knowledge to researchers, practitioners, and policymakers about the factors that influence youth intention to vote in Indonesia, namely, attitudes, perceived behavior control, and information from social media.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.759-766
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• 2021

In this digital age, all organizational environments force businesses to adopt Information and Communication Technologies (ICT) since these technologies have immense impact on such businesses' competitiveness and productivity. Nonetheless, the productivity and the competitiveness enjoyed by such firms vary depending on the size or the organizations, context of the country; developing or developed, and what kinds of technologies are adopted. This investigation focused on small- and medium-sized enterprises (SMEs) of Eastern province of Sri Lanka where such studies are scanty. The adoption of social media (SM) by SMEs is inclined to change how organizations operate, this calls for an investigation of the elements that impact SMEs to adopt SM and such investigation. Technology-Organization-Environment (TOE) framework was based to understand the factors. Research approach was quantitative approach using questionnaire survey. Data were collected using online form to see 285 valid responses. Structural Equation Modelling was deployed to evaluate the proposed model. Results revealed that Relative Advantage, Compatibility, Complexity, Observability, Competitive Intensity, Bandwagon Pressure, and Competitive Pressure were influencing, while Trialability, Top Management Support, CEO's Innovativeness did not show statistically significant influence on SMEs' social media adoption.

• Journal of People, Plants, and Environment
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• v.24 no.2
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• pp.209-218
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• 2021

Background and objective: Instagram, an image-based social media, is being used as an important outlet for the communication and place marketing of public spaces. The purpose of this paper was to analyze how types of place-based content affect user reactions (Likes and Comments) on Instagram in order to provide basic data on the operation and utilization of social media by public places such as botanical gardens and arboretums. Methods: A total of 850 posts uploaded to the Instagram account of Kew Gardens from November 6, 2014 to July 3, 2020 were classified using 14 subject codes. Multiple regression analysis was performed to evaluate the user's reaction between the dependent variables ("Likes", "Comments") and the independent variables (14 subject codes). Results: The findings showed that user reactions appear to differ depending on the typology of the content, and "Likes" and "Comments" were presented in independent behavioral reactions. In particular, "close-ups of plants (botanic, macro)," "plant colony (botanic, wide)," "place-specific landscape (building, landscape)," "anniversary" and "information" showed positive impacts on both "Likes" and "Comments"which could lead to electronic word-of-mouth and content sharing. Conclusion: Based on these findings, it can be argued that the typology of a botanical garden's content can be used to determine factors that affect the immediate reactions and enhance engagement with users.

• International Journal of Computer Science & Network Security
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• v.23 no.6
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• pp.202-206
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• 2023

Today, social media has become a vital tool. The world communicates and reaches the news and each other's opinions through social media accounts. Recently, considerable research has been done on analyzing social media due to its rich data content. At the same time, since the beginning of the COVID-19 pandemic, which has afflicted so many around the world, the search for a vaccine has been intense. There have been many studies analyzing people's feelings during a crisis. This study aims to understand people's opinions about available Coronavirus vaccines through a learning model that was developed for this purpose. The dataset was collected using Twitter's streaming Application Programming Interface (API) , then combined with another dataset that had already been collected. The final dataset was cleaned, then analyzed using Python. Polarity and subjectivity functions were used to obtain the results. The results showed that most people had positive opinions toward vaccines in general and toward the Pfizer one. Our study should help governments and decision-makers dispel people's fears and discover new symptoms linked to those listed by the World Health Organization.

• Knowledge Management Research
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• v.22 no.4
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• pp.1-26
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• 2021

Measuring the intangible asset has been vigorously studied for its importance. Especially, the value of character in media industry is difficult to quantitatively evaluate in spite of the industry's rapid growth. Recently, the Social Network Analysis (i.e., SNA) has been actively applied to understand human usage patterns in a media field. By using SNA methodology, this study attempts to investigate how the character network characteristics of media works are linked to human search behaviors. Our analysis reveals the positive correlation and causality between character network centralities and character search data. This result implies that the character network can be used as a clue for the valuation of character assets.

• International Journal of Contents
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• v.14 no.4
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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.

• Journal of the Korean Society of Clothing and Textiles
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• v.35 no.8
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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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• 2009.02a
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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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• v.15 no.3
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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.