• Journal of Information Science Theory and Practice
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• v.9 no.1
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• pp.68-78
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• 2021

Political weblogs are as diverse as political viewpoints are. In the period of Prime Minister Yingluck Shinawatra, several political crises occurred, such as opposition to the Amnesty Act, the constitutional amendment, and the anti-government protests. Remarkably, during this time, social media were used as a platform for political expressions. This study employed a content analysis method to explore twenty-nine Thai political weblogs established during the period of Prime Minister Yingluck Shinawatra's administration. At the time, the most prominent Thai political weblogger was Nidhi Eawsriwong. Not surprisingly, the Pheu Thai Party and the Democrat Party were the most frequently appearing political parties in these weblog's posts. Most contents in these posts were related to government protesters by the People's Democratic Reform Committee (PDRC) and the coup d'état. The purposes of writing such weblogs were to express feelings and thoughts about Thai politics and to provide political information to the general public. The findings from this investigation revealed two significant uses of Thai political weblogs: the communication media for political expressions and viewpoints (a safe online space for political engagement and participation), and vital sources for Thai political information and news (social narratives).

• Journal of Distribution Science
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• v.20 no.5
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• pp.35-47
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• 2022

Purpose: To explain the effect of product quality, price perception, online distribution, and social media promotion on attitudes, customer satisfaction, and local brand love. Research design, data and methodology: The population of this study are Indonesians who have purchased local Indonesian brand products. The size of the sample used was 240 people with purposive sampling method. The analytical technique used is Path Analysis using SEM-PLS. Results: product quality, price perception, online distribution have a positive effect on attitudes, but social media promotion has a positive and insignificant effect on consumer attitudes; product quality, price perception, online distribution, and social media promotion have a positive and significant effect on customer satisfaction, and attitudes have a positive and significant effect on local brand love; and customer satisfaction has a positive effect on brand love for local brands. Conclusion: Therefore, it is important for local brand product businesses to pay attention to product quality, price perception, online distribution, and social media promotion in order to be able to build positive attitudes, customer satisfaction and ultimately have an impact on local brand love. In online distribution, with online distribution, it is easy for marketers to deliver multimedia content through online methods.

• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.155-166
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• 2018

These days, online media, such as blogospheres, online communities, and social networking sites, provides the uncountable user-generated content (UGC) to discover market intelligence and business insight with. The business has been interested in consumers, and constantly requires the approach to identify consumers' opinions and competitive advantage in the competing market. Analyzing consumers' opinion about oneself and rivals can help decision makers to gain in-depth and fine-grained understanding on the human and social behavioral dynamics underlying the competition. In order to accomplish the comparison study for rival products and companies, we attempted to do competitive analysis using text mining with online UGC for two popular and competing ramens, a market leader and a market follower, in the Korean instant noodle market. Furthermore, to overcome the lack of the Korean sentiment lexicon, we developed the domain specific sentiment dictionary of Korean texts. We gathered 19,386 pieces of blogs and forum messages, developed the Korean sentiment dictionary, and defined the taxonomy for categorization. In the context of our study, we employed sentiment analysis to present consumers' opinion and statistical analysis to demonstrate the differences between the competitors. Our results show that the sentiment portrayed by the text mining clearly differentiate the two rival noodles and convincingly confirm that one is a market leader and the other is a follower. In this regard, we expect this comparison can help business decision makers to understand rich in-depth competitive intelligence hidden in the social media.

• Korean journal of communication and information
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• v.81
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• pp.299-328
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• 2017

This study investigated news comprehension via the social media by comparing the reading of a news story on the news paper. A news story on the social media was suggested to present information in a conversational form, which differs from a traditional reporting style. To compare the different forms of news information presentation, two conditions were created: in a control condition, a news story was written in a traditional reporting form. In the experimental condition, the same news story was constructed in a conversational form. Participants were assigned randomly in one of two conditions. They read the news story and afterwards, they were asked to recall firstly, the core idea of the news story, secondly the whole news story, and finally to answer to the 10 questions that assessed how well they learned from the news story. Participants' responses were content-analyzed and produced six variables, the extent to recall the core idea, the extent to recall the whole story, the extent to recall wrong information, the extent to recall additional information, the extent to recall causally related contents in general, and finally the extent to recall causally related contents in story-specific. Analyses on the six variables revealed that the group in the news paper condition recalled more core idea, the whole story, and additional information than the group in the social media. But the news paper condition recalled less of wrong information than the group in the social media condition. Additionally, the news paper condition learned more than the group in the social media. Regarding the recall of causally related contents, the general causal relationships were recalled more in the group in the social media condition but the story specific causal relationships were recalled more in the group in the news paper condition. The findings seemingly indicated that a traditional news reporting contributes to news story comprehension more than the conversational form. Authors however added discussions and advised that the findings needed to be read under caution.

• Journal of Information Technology Applications and Management
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• v.27 no.4
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• pp.49-62
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• 2020

In this study, the research model of VR·AR contents convergence education for solving social problems was presented after benchmarking the domestic and foreign realistic educational contents industry and policy trends and Fishbone diagram analysis. The goal was to create VR·AR content convergence talent for co-prosperity in the era of the fourth industrial revolution, and the target of education was students, researchers, and business personnel who are interested in VR AR technology education and contents business such as game animation, etc. The education model is based on understanding about storytelling of the socially disadvantaged, such as children and the elderly, and is technology education for content production including the application of virtual and augmented reality SW, and is a convergence education for content planning and business model strategy development.

• International journal of advanced smart convergence
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• v.11 no.2
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• pp.95-101
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• 2022

The development of the 4th industry has increased social media, and the rise of COVID-19 has stimulated non-face-to-face services. People's consumption patterns are also changing a lot due to non-face-to-face services. In this paper, food content keywords are derived through social network-based semantic network analysis, emotions are analyzed, and keywords applied to food recommendation platforms are input. We collected food, influencer, and corona keyword analysis data through Textom. A lot of research has been done through online reviews of existing influencer content. However, there is a lack of research on keyword sentiment analysis provided by influencers rather than consumers and research perspectives. This paper uploads language and topics derived through online reviews of existing publications and subscribers, and goes beyond the limits used in marketing methods. By analyzing keywords that influencers suggest when uploading content, you can apply data that applies them to food recommendation platforms and applications.

• Korean journal of communication and information
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• v.60
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• pp.172-192
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• 2012

Over the last ten years, media convergence and multiple platform expansion have affected the ways that people watch conventional television. In the post-TV era, the growing use of the Internet and mobile multi-media devices, such as smart phones, as well as the availability of abundant television content, allows television consumption to be more personalized, diversified, and linked with various media activities, especially social media uses. This study attempts to examine how television viewing experiences have been transformed with the development of the trans-media uses. Based on Walter J. Ong's concept of relation-ism, which posits that new media transform the meanings and relevance of old media rather than making old media obsolete, this study will pay particular attention to how the cultural meanings of television viewing have been redefined in the post-TV era. For the examination, this study has looked at concrete cases of the television viewing experiences of 29 young people in their twenties. Based on in-depth interview data, this study discusses the newly emerging characteristics of television viewing, its temporal and spatial experiences, and the significance of television as a medium and as a social place.

• Knowledge Management Research
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• v.22 no.4
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• pp.217-235
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• 2021

As 49% of the world's population uses social media platforms, communication and content sharing within social media are becoming more active than ever. In this environmental base, the one-person media market grew rapidly and formed public opinion, creating a new trend called sell-sumer. This study defined new types of influencers by product category by analyzing the subject concentration of the commercial/non-commercial keywords of influencers and the impact of the ratio of commercial postings on sales. It is hoped that influencers working within social media will be helpful to new sales strategies that are transformed into sell-sumers. The method of this study classifies influencers' commercial/non-commercial posts using Python, performs text mining using KoNLPy, and calculates similarity between FastText-based words. As a result, it has been confirmed that the higher the keyword theme concentration of the influencer's commercial posting, the higher the sales. In addition, it was confirmed through the cluster analysis that the influencer types for each product category were classified into four types and that there was a significant difference between groups according to sales. In other words, the implications of this study may suggest empirical solutions of social media sales strategies for influencers working on social media and marketers who want to use them as marketing tools.

• International Journal of Knowledge Content Development & Technology
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• v.5 no.1
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• pp.15-32
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• 2015

This article analyzes motivations behind social sciences blog posts citing journal articles in order to find out whether blog citations are good indicators for the societal impact or benefits of research. A random sample of 300 social sciences blog posts (out of 1,233 blog posts) from ResearchBlogging.org published between 01/01/2012 to 18/06/2014 were subjected to content analysis. The 300 blog posts had 472 references including 424 journal articles from 269 different journals. Sixty-one (22.68%) of all cited journals were from the social sciences and most of the journals with high frequency were highly cited general science journals such as PNAS and Science. Seventy-five percent of all journals were referenced only once. The average age of articles cited at the time of citation was 5.8 years. Discussion and criticism were the two main categories of motivations. Overall, the study shows the potential of blog citations as an altmetric measure and as a proxy for assessing the research impact. A considerable number of citation motivations in blogs such as disputing a belief, suggesting policies, providing a solution to a problem, reacting to media, criticism and the like seemed to support gaining societal benefits. Societal benefits are considered as helping stimulate new approaches to social issues, or informing public debate and policymaking. Lower self-citation (compared to some other altmetric measures such as tweets) and the fact that blogging involves generating content (i.e. an intellectual process) give them an advantage for altmetrics. However, limitations and contextual issues such as disciplinary differences and low uptake of altmetrics, in general, in scholarly communication should not be ignored when using blogs as a data source for altmetrics.

• Korean journal of communication and information
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• v.30
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• pp.35-87
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• 2005

This research explores the empirical confirmation of the Internet development including from the period of innovation to the time of social-cultural use in today. The research focused on how tradition news media rover about the Internet developed from early to today, and understanding the media characteristics on the each stages from news frame. The research Is designed to conduit content analysis from 1989 to 2004, then this research is divided four(4) stages of the Internet development: innovation, diffusion, commercial usage, social-cultural usage. The results shows that there are significant different coverage by the stages. First of all, the news coverage pattern shift from technology focused on early stages to social usage focused on the later stages. This research confirms that the ratio of the seriation(technology) coverage defined when social usage is increased, on the other hand skeumorphs(social usage and content) coverage is increased in the commercial and social usage stages. This coverage pattern among news media does not such a big different and there is no competitive coverage. Moreover, the news coverage shifted from thematic coverage on early stages to episodic coverage while the number of usage increasing. In addition, the tone of coverage has not been changed significantly.