• International Journal of Contents
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• v.9 no.1
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• pp.49-59
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• 2013

This study explores how Twitter users perceive their socio-communication attitudes as well as those who users follow. From the theoretical perspective of communication styles in interpersonal communication, this study focuses on the positions and roles of users and their partners in Twitter conversations by conducting a survey and a content analysis. The results demonstrate that the respondents tended to perceive their communication attitudes to be more passive on Twitter than in the real world. In addition, they tended to perceive that their most trusted followees were more likely to show dominant communication attitudes than they did. These results indicate that ordinary users are more likely to play a role as listeners than as speakers on Twitter while entrusting several trusted users with the role of a dominant communicator and that their perception of their own and their followees' communication styles tends to influence their actual behavior on Twitter.

• Journal of Contemporary Eastern Asia
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• v.12 no.1
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• pp.65-79
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• 2013

This paper examines communication patterns of key Twitter users by considering the socially and politically controversial Sejong City issue in South Korea. The network and message data were drawn from twtkr.com. Social network-based indicators and visualization methods were used to analyze political discourse among key Twitter users over time and illustrate various types of Tweets by these users and the interconnection between these key users. In addition, the study examines general Twitter users' participation in the discussion on the issue. The results indicate that some Twitter profiles of media outlets tend to be very dominant in terms of their message output, whereas their Tweets are not likely to be circulated by other users. Noteworthy is that Twitter profiles of individuals who are geographically affiliated with the issue are likely to play an important role in the flow of communication.

• Journal of Information Science Theory and Practice
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• v.7 no.4
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• pp.33-44
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• 2019

Altmetrics measure the frequency of references about an article on social media platforms, like Twitter. This paper studies a variety of factors that affect the popularity of articles (i.e., the number of article mentions) in the field of psychology on Twitter. Firstly, in this study, we classify Twitter users mentioning research articles as academic versus non-academic users and experts versus non-experts, using a machine learning approach. Then we build a negative binomial regression model with the number of Twitter mentions of an article as a dependant variable, and nine Twitter related factors (the number of followers, number of friends, number of status, number of lists, number of favourites, number of retweets, number of likes, ratio of academic users, and ratio of expert users) and seven article related factors (the number of authors, title length, abstract length, abstract readability, number of institutions, citation count, and availability of research funding) as independent variables. From our findings, if a research article is mentioned by Twitter users with a greater number of friends, status, favourites, and lists, by tweets with a large number of retweets and likes, and largely by Twitter users with academic and expertise knowledge on the field of psychology, the article gains more Twitter mentions. In addition, articles with a greater number of authors, title length, abstract length, and citation count, and articles with research funding get more attention from Twitter users.

• Journal of the Korea Society of Computer and Information
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• v.21 no.3
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• pp.73-81
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• 2016

With the increasing popularity of social network services (SNSs), there have been many attempts to analyze the users of SNSs. By doing so, the characteristics and preferences of the users can be understood, which can help companies provide personalized information and services that they need or are relevant for them. This study aimed to analyze the usage behavior of Korean Twitter users from various perspectives to deepen the understanding of it. For this research goal, an online survey was conducted for the users of Twitter and the data about their actual usage were collected using the open API of Twitter. Factor analysis of the data revealed five factors that explain about 69.3% of the usage variables. It was also investigated how the factors are related to gender, age, and brand preferences. The results showed that the usage behavior of Twitter is largely affected by age (p<0.001), and also by gender through an interaction effect (p<0.05). Also, the factors showed significant statistical correlations with the brand preferences of the users.

• Journal of information and communication convergence engineering
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• v.10 no.2
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• pp.135-140
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• 2012

Massive numbers of users of social networks share various types of information such as opinions, news, and ideas in real time. As a new form of social network, Twitter is a particularly useful information source. Studying influence can help us better understand the role of social networks. The popularity of social networks like Twitter is primarily measured by the number of followers. The number of followers in Twitter and the number of users exposed to news media are important factors in measuring influence. We chose Twitter and the New York Times as representative media to analyze the influence and present an empirical analysis of these datasets. When the correlation between the number of followers in Twitter and the number of users exposed to the New York Times is computed, the result is moderately high. The correlation between the number of users exposed to the New York Times and the number of sections including the users on it, was found to be very high. We measure the normalized influence score using our proposed expression based on the two correlation coefficients.

• Journal of Korea Multimedia Society
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• v.15 no.7
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• pp.910-919
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• 2012

We have observed huge success in social network services like Facebook and Twitter, and many researchers have done their analysis on these services. As massive data observed by users is produced on Twitter, many researchers have been conducting research to detect an event on Twitter. Some of them developed a system to detect the earthquakes or to find the local festivals. However, they did not consider the credibility of location information on Twitter although their systems were using the location information. In this paper, we analyze the credibility of the profile location and the correlation between the spatial attributes on Twitter as the preliminary research of the event detection system on Twitter. We analyzed 0.5 million Twitter users in Korea and 2.8 million users around the world. 49.73% of the users in Korea and 90.64% of the users in the world posted tweets in their profile locations. This paper will be helpful to understand the credibility of the spatial attributes on Twitter when the researchers develop an application using them.

• 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 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 Information Technology Services
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• v.10 no.4
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• pp.149-169
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• 2011

As the number of smart phone users increases, many organizations begin to adopt social media rapidly to diversify communication channels with customers. Specifically, twitter, which supports instant and two-way communications between users and between organizations and users, has been adopted by many organizations as an efficient way not only to identify new customers but also to retain existing customers. However, little attention has been given to the issue on how organizations can effectively use twitter to improve customer satisfaction. To explore the issue, this study proposes two major dimensions, customer participation and organization resource utilization, which should be considered in building a utilization strategy for twitter in organizations. We then develop four different combinations along with these dimensions-follow, mention, retweet, and review types. Based on case studies of 27 organizations that use twitter, we evaluate the degrees of customer participation, resource utilization, and customer satisfaction, and examine matching or mismatching of the adoption purpose of twitter and its actual utilization. The study results reveal that organizations in the matching group show higher customer satisfaction that those in the mismatching group. This study sheds new light on twitter research by developing a new conceptual framework and using a case study approach to explore the relationship between the utilization strategy of twitter and customer satisfaction.

• 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.