• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.89-107
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• 2021

This paper explores the empirically analyzes the competitive nature of the five social media by analyzing the proper SNS service such as Facebook, Instagram, YouTube, Pinterest, and Twitter. In this study, we surveyed the use and satisfaction of social media for SNS users by using the proper theory. A total of 224 users were selected for analysis. Based on the results of the questionnaire, factor analysis was carried out to extract common factors such as relationship, sociality, convenience, daily life, and entertainment. As a result of the research using proper analysis, Facebook showed the widest narrowness in sociality (.627) and convenience (.636) in the first place, and YouTube showed the lowest in daily life (.670) and entertainment (.615) In the relationship (.520), the Instagram was the widest. In terms of five factors, Facebook and YouTube have the greatest overlap in relationship (1.826) and sociality (2.696), while Pinterest and Twitter are the most common in daily life (1.937) and entertainment (2.263) There is redundancy, and for convenience (2.583), YouTube and Twitter have the most redundancy. Facebook, Instagram, and YouTube have a competitive advantage over Pinterest in terms of relationships, sociality, convenience, routine, and entertainment, and are competitive across all factors except Facebook, Instagram, and YouTube Twitter It is possible to confirm that it is superior.

• 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 the Korean Society of School Health
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• v.25 no.1
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• pp.133-142
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• 2012

Purpose: The purpose of this study is to identify the effects of suicide reports by mass media and social support on suicide ideation for college students. Methods: Participants are 350 undergraduate students in one university. This study uses three questionnaires: Perception and Attitude toward Suicide Reports, Social Support, and Suicidal Ideation. The SPSS/WIN 12.0 program is used to analyze the data. In particular, the participants' biographical data are analyzed into frequency and percentage. The degrees of suicide reports, social support, and suicide ideation are calculated into Mean and SD. Moreover, the suicide ideation by suicide report and social support are analyzed by the two-way analysis of variance (ANOVA). Results: This study reveals that college students have an average of 30 minutes to one hour news time a day (38.9%) and have at least one suicide report in a month (30.3%). 79.7% participants believe that the suicide report of mass media results in the cause of the copycat suicide. In terms of suicide report and suicide ideation, the types of mass media (F (4,340)=2.41, p<.05) and suicidal urge (F (1,340)=31.23, p<.01), respectively, have significant influences on suicide ideation. On the other hand, the social support and suicide ideation, whether college students have their mentors (F (1,328)=13.26, p<.001) and/or careres (F (1,328)=26.84, p<.001) have significant influences on suicide ideation. Conclusion: College students have higher suicide ideation at news by internet site rather than by radio, TV, and so on. Moreover, college students who have a suicide feeling in the last one year, have more suicide ideation than who have not. On the other hand, college students who have a mentor and carer tend to have less suicide ideation.

• Human Ecology Research
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• v.60 no.1
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• pp.21-38
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• 2022

This study uses text mining compares and contrasts consumers' social media discourses on dietary related zero-waste movement before and after COVID-19. The results indicate that the amount of buzz on social networks for the zero- waste movement has been increasing after COVID-19. Additionally, the results of frequency analysis and topic modeling revealed that subjects associated with zero-waste movement were more diversified after COVID-19. Although the results of a sentiment analysis and word cloud visualization confirmed that consumers' positive responses toward the zero-waste have been increasing, they also revealed a need to educate and encourage those who are still not aware of the need for zero-waste. Finally, consumers mentioned only a small number of companies participating in zero-waste movement on SNS, indicating that the level of active involvement by such companies is much lower than that of consumers. Theoretical and educational implications as well as those for government policy-making are considered.

• International Journal of Advanced Culture Technology
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• v.8 no.3
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• pp.247-253
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• 2020

It has emerged Food-content among various forms of 1-person media through social media. Food-content influencer also market products through 1-person media, generating revenue through increased views and subscribers of 1-person media. It also sells products through sponsorship. In general, there is a profit structure through 1-person media viewing, but research on how restaurant companies generate profits directly through food-content is insufficient. In addition, research on converting subscribers to consumers through food-contents is minimal. In this paper, we propose an experiential application system based on the behavior of food-content creators. The proposed system collects and categorizes food-content information, and maps between highly related words to organize into keyword categories. The ontology tag-based concept network applied to the proposed system connects representative information by pre-extracting/mapping information related to information requests among a wide range of data. This method maps relevant food-content information to provide the user with data collected/storage in the form of an application. The user uses the application while watching the food eaten by the influencer and creator. And, it is meaningful that the user could be provided is provided with information about the food they want to eat.

• Journal of Digital Convergence
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• v.18 no.2
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• pp.249-259
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• 2020

This study presents a recently obtained social media data set based upon the case study of Electric Vehicles (EV) and looks to implement a sentiment analysis (SA) in order to gain insights. This study uses two methods in order to fully analyze the public's sentiment on EVs. First, we implement a SA tool in which we used to extract the sentiment of comments. Next we labeled the data with these sentiments obtained and classified them. While performing classification we found the problem of dimensionality and also explored the use of feature selection (FS) models in order to reduce the data set's dimensionality. We found that the use of three FS models (Chi Squared, Information Gain and ReliefF) showed the most promising results when used alongside a logistic and support vector machines classification algorithm. the contributions of this paper are in providing an real-world example of social media text analytics which can be adopted in many other areas of research and business. Moving forward researchers can use the methodological approach in this paper to further refine and improve their own case uses in text analytics.

• Korea Journal of Hospital Management
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• v.15 no.1
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• pp.70-92
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• 2010

Now more than ever, many journalists are using hospitals' homepages for articles about hospitals, their mission, research, and events. Therefore hospitals' homepages have to be planned and constructed for journalists. The purpose of this study is to investigate hospitals' online media relations through analysing homepages. For investigating specifically, this study compares hompages of hospitals in Korea and hospitals in USA. This study uses four categories; basic media relations tools, useful information, interactive communication tools, and ease of use for journalists. The result of this study shows that hospitals' homepages in Korea are needed to improve for building with journalists. The hospitals' hompages have to be constructed by a variety of materials; press room, image and graphic archives, multimedia resources, and interactivity or responsiveness. This study suggests that the hospitals' homepages have the potential to achieve the desired public relations objective but are not commonly being used to their full potential in media relations.

• The Research Journal of the Costume Culture
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• v.29 no.4
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• pp.603-615
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• 2021

The aim of this study was to analyze the semantic network structure of keywords and the visual composition of images extracted from Instagram in relation to the multi-persona phenomenon with in fashion imagery, which has recently been attracting attention. To this end, the concept of a 'secondary character', which forms a separate identity from a 'main character' on various social media platforms as well as on the airwaves, was considered as the spread of multi-persona and #SecondaryCharacter on Instagram was investigated. 3,801 keywords were collected after crawling the data using Python and morphological analysis was undertaken using KoNLP. The semantic network structure was then examined by conducting a CONCOR analysis using UCINET and Netdraw to determine the top 50 keywords. The results were then classified into a total of 6 clusters. In accordance with the meaning and context of the keywords included in each cluster, group names were assigned : virtual characters, relationship with the main character, hobbies, daily record, N-job person, media and marketing. Image analysis considered the technical, compositional, and social styles of the media based on Gillian Rose's visual analysis method. The results determined that Instagram uses fashion images that virtualize one's face to produce multi-persona representation s that show various occupations, describe different types of hobbies, and depict situations pertaining to various social roles.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.4
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• pp.780-786
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• 2015

Social media, such as Social Network Service include a lot of spontaneous opinions from customers, so recent companies collect and analyze information about customer feedback by using the system that analyzes Big Data on social media in order to efficiently operate businesses. However, it is difficult to analyze data collected from online sites accurately with existing morpheme analyzer because those data have spacing errors and spelling errors. In addition, many online sentences are short and do not include enough meanings which will be selected, so established meaning selection methods, such as mutual information, chi-square statistic are not able to practice Emotional Classification. In order to solve such problems, this paper suggests a module that can revise the meanings by using initial consonants/vowels and phase pattern dictionary and meaning selection method that uses priority of word class in a sentence. On the basis of word class extracted by morpheme analyzer, these new mechanisms would separate and analyze predicate and substantive, establish properties Database which is subordinate to relevant word class, and extract positive/negative emotions by using accumulated properties Database.