• Journal of Internet Computing and Services
• /
• v.15 no.1
• /
• pp.89-102
• /
• 2014

Since the Arab spring in 2010, SNS prompted discussions about the roles to organize collective actions. First of all, mobile media and SNS help to mobilize both on and offline social movement, second, to create new forms of collective actions, third, to organize social movement organizations across the world, fourth, to empower movement participants to develop new collective identities. On the other hand, the same technologies also hinder social movements from developing continuity and dedication. In addition, the problems of digital divide might aggravate the divisive process to organize collective actions across the world. This research is built on these ongoing arguments about the potentials and limitations of new media technologies. In particular, this research tries to move beyond the confrontational approaches to the media through the case study of Save The Jeju Island social movements on Facebook. The movement SNS on Facebook aims to provide as well as organize international SMOs and activists that might help deeper understandings on the potentials and limitations of online communication strategies for global social movements.

• Journal of Service Research and Studies
• /
• v.13 no.1
• /
• pp.26-47
• /
• 2023

In the age of digital media transformation, the rapid rise of social media has changed the paradigm of traditional marketing techniques by leveraging the influence of influencers. However, the influence of influencers cannot be freed from ethical issues that arise as individuals, so virtual influencers are emerging as a countermeasure. This study is a study on how to increase the influencer effect of virtual models with a focus on the MZ generation in medical service. This study investigated whether respondents in their 40s or younger were aware of 'Rosy', a virtual influencer, and then conducted a survey on those who recognized 'Rosy'. As a result of this study, first, both cognitive and emotional motivation had a positive influence on fanship and attractiveness for virtual influencer. In addition, it was found that there was a difference in follow motive according to gender. Second, in order to lead to the intention of visiting hospitals, which is the medical service industry, only the cognitive motives with useful and reliable information and useful information for the virtual influencer were found to be significant in intention to visit.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.3
• /
• pp.415-423
• /
• 2023

The purpose of this study was to prepare basic data for improving school library information service by investigating the information usage behavior of specialized high school students. Preferred information sources for each situation requiring information and the level of solving information problems using information sources were investigated, and difference analysis was conducted by department and grade. As a result of the survey, the percentage of students who preferred Internet portal services, personal information sources (teachers, friends, parents), and social media was high, while the percentage of students who preferred traditional print information sources and mass media was very low. The average score of the information problem solving level was 3.55, and the problem solving level in the areas of employment and career/admission was relatively low. Preferred sources of information were similar regardless of grade and department, and the difference between departments in information problem solving level was not statistically significant, but the difference between grades was statistically significant. In addition, there is an academic contribution in this field that specific examples of youth information use behavior have been added. Based on the results of the study, librarians should make efforts to verify the reliability of Internet portal site information, improve and promote library information sources, and expand library use education. In future studies, it was suggested to develop customized information services.

• Journal of Korea Entertainment Industry Association
• /
• v.14 no.6
• /
• pp.139-150
• /
• 2020

The data processing of this study focuses on the textom and social media words about three areas: 'Corona 19 and professional baseball', 'Corona 19 and professional baseball', and 'Corona 19 and professional sports' The data was collected and refined in a web environment and then processed in batch, and the Ucinet6 program was used to visualize it. Specifically, the web environment was collected using Naver, Daum, and Google's channels, and was summarized into 30 words through expert meetings among the extracted words and used in the final study. 30 extracted words were visualized through a matrix, and a CONCOR analysis was performed to identify clusters of similarity and commonality of words. As a result of analysis, the clusters related to Corona 19 and Pro Baseball were composed of one central cluster and five peripheral clusters, and it was found that the contents related to the opening of professional baseball according to the corona 19 wave were mainly searched. The cluster related to Corona 19 and unrelated to professional baseball consisted of one central cluster and five peripheral clusters, and it was found that the keyword of the position of professional baseball related to the professional baseball game according to Corona 19 was mainly searched. Corona 19 and the cluster related to professional sports consisted of one central cluster and five peripheral clusters, and it was found that the keywords related to the start of professional sports according to the aftermath of Corona 19 were mainly searched.

• Journal of Intelligence and Information Systems
• /
• v.20 no.1
• /
• pp.163-176
• /
• 2014

Social media is becoming the platform for users to communicate their activities, status, emotions, and experiences to other people. In recent years, microblogs, such as Twitter, have gained in popularity because of its ease of use, speed, and reach. Compared to a conventional web blog, a microblog lowers users' efforts and investment for content generation by recommending shorter posts. There has been a lot research into capturing the social phenomena and analyzing the chatter of microblogs. However, measuring television ratings has been given little attention so far. Currently, the most common method to measure TV ratings uses an electronic metering device installed in a small number of sampled households. Microblogs allow users to post short messages, share daily updates, and conveniently keep in touch. In a similar way, microblog users are interacting with each other while watching television or movies, or visiting a new place. In order to measure TV ratings, some features are significant during certain hours of the day, or days of the week, whereas these same features are meaningless during other time periods. Thus, the importance of features can change during the day, and a model capturing the time sensitive relevance is required to estimate TV ratings. Therefore, modeling time-related characteristics of features should be a key when measuring the TV ratings through microblogs. We show that capturing time-dependency of features in measuring TV ratings is vitally necessary for improving their accuracy. To explore the relationship between the content of microblogs and TV ratings, we collected Twitter data using the Get Search component of the Twitter REST API from January 2013 to October 2013. There are about 300 thousand posts in our data set for the experiment. After excluding data such as adverting or promoted tweets, we selected 149 thousand tweets for analysis. The number of tweets reaches its maximum level on the broadcasting day and increases rapidly around the broadcasting time. This result is stems from the characteristics of the public channel, which broadcasts the program at the predetermined time. From our analysis, we find that count-based features such as the number of tweets or retweets have a low correlation with TV ratings. This result implies that a simple tweet rate does not reflect the satisfaction or response to the TV programs. Content-based features extracted from the content of tweets have a relatively high correlation with TV ratings. Further, some emoticons or newly coined words that are not tagged in the morpheme extraction process have a strong relationship with TV ratings. We find that there is a time-dependency in the correlation of features between the before and after broadcasting time. Since the TV program is broadcast at the predetermined time regularly, users post tweets expressing their expectation for the program or disappointment over not being able to watch the program. The highly correlated features before the broadcast are different from the features after broadcasting. This result explains that the relevance of words with TV programs can change according to the time of the tweets. Among the 336 words that fulfill the minimum requirements for candidate features, 145 words have the highest correlation before the broadcasting time, whereas 68 words reach the highest correlation after broadcasting. Interestingly, some words that express the impossibility of watching the program show a high relevance, despite containing a negative meaning. Understanding the time-dependency of features can be helpful in improving the accuracy of TV ratings measurement. This research contributes a basis to estimate the response to or satisfaction with the broadcasted programs using the time dependency of words in Twitter chatter. More research is needed to refine the methodology for predicting or measuring TV ratings.