• Journal of Information Technology Applications and Management
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• v.20 no.2
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• pp.109-125
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• 2013

As the number of SNS users is increasing, it has been very important how companies use SNS strategically. As a result, studies have been performed for the utilization of SNS. Most of the studies, however, focused on the overall characteristics of SNS and did not consider the characteristics of individual SNS. This study classified the main purpose of SNS use as relation-oriented purpose and information-oriented purpose, and identified the types of SNS from two viewpoints : service type and openness. Based on the classification, this study identified the characteristics of Cyworld, Facebook, and Twitter respectively, and analyzed the difference of the purpose of SNS users according to the characteristics of each service. The results showed that more users had the information-oriented purpose in the order of Twitter, Facebook, and Cyworld. There was no difference in the relation-oriented purpose among the three services. The analyses of the motive to join a group or a party made similar results. The results of additional analyses showed that the ratio of users with many acquaintances was high in the order of Facebook, Twitter, and Cyworld. In addition, more users checked their timeline or news feed more frequently in the order of Facebook, Twitter, and Cyworld.

• Journal of Information Management
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• v.43 no.2
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• pp.133-150
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• 2012

This study showed the activation of public library services utilizing twitter. Top five American public library twitter's 1,373 tweets collected, analyzed by content types and examined applicability into public library services. Based on the results, it suggested that public library services can be activated by auto-tweeting informations within home page, re-tweeting of timely informations, generating HASH tag, using diverse social medias, active re-tweeting/replying, and utilizing twitter programs such as twit-bot. Finally, the study proposed that evaluations about twitter services such as satisfaction survey should be carried out.

• 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.

• Journal of the Korea Society of Computer and Information
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• v.27 no.2
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• pp.53-60
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• 2022

YouTube realistically shows fake news and biased content based on facts that have not been verified due to low entry barriers and ambiguity in video regulation standards. Therefore, this study aims to analyze the influence of the media and YouTube on individual behavior and their relationship. Data from YouTube and Twitter are randomly imported with selenium, beautiful soup, and Twitter APIs to classify the 31 most frequently mentioned keywords. Based on 31 keywords classified, data were collected from YouTube, Twitter, and Naver News, and positive, negative, and neutral emotions were classified and quantified with NLTK's Natural Language Toolkit (NLTK) Vader model and used as analysis data. As a result of analyzing the correlation of data, it was confirmed that the higher the negative value of news, the more positive content on YouTube, and the positive index of YouTube content is proportional to the positive and negative values on Twitter. As a result of this study, YouTube is not consistent with the emotion index shown in the news due to its secondary processing and affected characteristics. In other words, processed YouTube content intuitively affects Twitter's positive and negative figures, which are channels of communication. The results of this study analyzed that YouTube plays a role in assisting individual discrimination in the current situation where accurate judgment of information has become difficult due to the emergence of yellow media that stimulates people's interests and instincts.

• The Journal of the Korea Contents Association
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• v.13 no.11
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• pp.138-147
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• 2013

This study aims to explore how journalistic norms are practiced in journalists tweets by analyzing journalists' twitter. The study found that journalists consider using twitter as an extension of journalistic practice rather than a private space. In other words, journalists use twitter without a clear distinction about the nature of the twitter. In terms of journalistic norms, journalists expressed actively their opinion rather than keeping the traditional notion of objectivity. There are not much tendency of sharing the gatekeeping role. Also, journalistic use of twitter does not increase transparency as much as expected. However, there is a positive sign of practicing the newly expected journalistic role, conversation with news users. Finally the relationships between journalistic use of twitter and journalistic norms are not straightforward but diverse depending on the size and type of press, and gender of journalists.

• Journal of Internet Computing and Services
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• v.15 no.5
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• pp.63-72
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• 2014

Twitter has been a popular social media platform where people post short messages of 140 characters or less via the web. A hashtag is a word or acronym created by Twitter users to open a discussion about certain topics and issues that have a very high percentage of trending. Since the hashtag posts are sorted by time, not relevancy, people who firstly use Twitter have had difficulty understanding their context. In this paper, we propose a HBase-based automatic summary system in order to reduce the difficulty of understanding. The proposed system combines an automatic summary method with a fuzzy system after storing the streaming data provided by Twitter API to the HBase. Throughout this procedure, we have eliminated the duplicate of contents in the hashtag posts and have computed scores between posts so that the users can access to the trending topics with relevancy.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.67-101
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• 2014

The use of new technology greatly shapes the marketing strategies used by companies to engage their consumers. Among these new technologies, social media is used to reach out to the organization's audience online. One of the most popular social media channels to date is the microblogging platform Twitter. With 500 million tweets sent on average daily, the microblogging platform is definitely a rich source of data for researchers, and a lucrative marketing medium for companies. Nonetheless, one of the challenges for companies in developing an effective Twitter campaign is the limited theoretical and empirical evidence on the proper organizational usage of Twitter despite its potential advantages for a firm's external communications. The current study aims to provide empirical evidence on how firms can utilize Twitter effectively in their marketing communications using the association between brand personality and brand engagement that several branding researchers propose. The study extends Aaker's previous empirical work on brand personality by applying the Brand Personality Scale to explore whether Twitter brand communities convey distinctive brand personalities online and its influence on the communities' level or intensity of consumer engagement and sentiment quality. Moreover, the moderating effect of the product involvement construct in consumer engagement is also measured. By collecting data for a period of eight weeks using the publicly available Twitter application programming interface (API) from 23 accounts of Twitter-verified business-to-consumer (B2C) brands, we analyze the validity of the paper's hypothesis by using computerized content analysis and opinion mining. The study is the first to compare Twitter marketing across organizations using the brand personality concept. It demonstrates a potential basis for Twitter strategies and discusses the benefits of these strategies, thus providing a framework of analysis for Twitter practice and strategic direction for companies developing their use of Twitter to communicate with their followers on this social media platform. This study has four specific research objectives. The first objective is to examine the applicability of brand personality dimensions used in marketing research to online brand communities on Twitter. The second is to establish a connection between the congruence of offline and online brand personalities in building a successful social media brand community. Third, we test the moderating effect of product involvement in the effect of brand personality on brand community engagement. Lastly, we investigate the sentiment quality of consumer messages to the firms that succeed in communicating their brands' personalities on Twitter.

• Journal of Information Science Theory and Practice
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• v.5 no.3
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• pp.48-60
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• 2017

The purpose of this paper is to understand the profiles of users and their motivations in sharing research articles on Twitter. The goal is to contribute to the understanding of Twitter as a new altmetric measure for assessing impact of research articles. In this paper, we extended the previous study of tweet motivations by finding out the profiles of twitter users. In particular, we examined six characteristics of users: gender, geographic distribution, academic, non-academic, individual, and organization. Out of several, we would like to highlight here three key findings. First, a great majority of users (86%) were from North America and Europe indicating the possibility that, if in general, tweets for research articles are mainly in English, Twitter as an alternative metric has a Western bias. Second, several previous altmetrics studies suggested that tweets, and altmetrics in general, do not indicate scholarly impact due to their low correlation with citation counts. This study provides further details in this aspect by revealing that most tweets (77%) were by individual users, 67% of whom were nonacademic. Therefore, tweets mostly reflect impact of research articles on the general public, rather than on academia. Finally, analysis from profiles and motivations showed that the majority of tweets (from 42% to 57%) in all user types highlighted the summary or findings of the article indicating that tweets are a new way of communicating research findings.

• Journal of Information Technology Services
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• v.11 no.3
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• pp.49-65
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• 2012

This study aims to investigate the factors influencing followers' continuous usage intention of twitter based on Elaboration Likelihood Model. In particular, central route(information itself) and peripheral route(twitterian's trustworthiness) are tested to reveal which has a more influential role in effecting the continuous usage intention of power-twitter. Furthermore, this study tests the relationship of users' attitude and continuous usage intention. The results indicate that argument quality, accuracy(central route), source expertise and source trustworthiness (peripheral route) have an influence on attitude. However, trustworthy on central route is not significant. Argument quality, trustworthy, accuracy(central route) and source expertise(peripheral route) have an influence on perceived usefulness. But source trustworthiness on peripheral is not significant. Attitude has an influence on perceived usefulness, and attitude and perceived usefulness both have an influence on perceived usefulness. In conclusion, central route is more influential than peripheral route in forming a positive attitude towards arguments, which in turn leads to the perception of twitter's usefulness, and in the end brings the continuous usage intention of twitter.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.7
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• pp.814-818
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• 2010

Online social networking services help people to migrate social networks from offline to online. Twitter, which has achieved incredible growth, showed that an online social networking service without offline bases can become large and successful. In this paper, we propose a twitter friend notification service using user‘s twitter messages and place recognizing technology. When there is a friend in user‘s nearby place, the service notifies the information to the users. Through the friend notification service, a user can easily extend his online social network to offline.