• Journal of Information Technology Applications and Management
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• v.19 no.2
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• pp.197-215
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• 2012

SNS has been recognized as a means of expanding social capital by promoting interaction and efficient communication among users. On the other hand, there are serious concerns on negative side of social network which is often called epidemics. Trust plays a critical role in controlling the spread of distorted information and vicious rumor as well as reducing uncertainties and risk from unreliable users in social network. This study focuses on what the antecedents of interpersonal trust are in social network. We performed online survey from 252 Twitter users and tested candidate antecedents which are chosen from previous literature. As a result, propensity to trust of trustor, ability and sincerity of trustee, intimacy between trustor and trustee significantly affected to the interpersonal trust in Twitter.

• The Journal of Information Systems
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• v.21 no.1
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• pp.69-91
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• 2012

The study investigates the media distinctiveness between twitter and other social media and describes how product information interpretation and responsiveness by internet users can be affected by the distinctive characteristics of twitter and blog media. The characteristics include relationship formation patterns among users, channel diversity, immediateness of information communication, information flow within media, media credibility, and management cost. Specifically, we statistically tested whether these characteristics are meaningfully differentiated by users. Results also showed that users perceived product information processing level and product evaluation direction differently based on these media characteristics. The current findings can serve as a pioneering work to provide a theoretical framework for examining social media characteristics and their impacts on consumer perception. In addition, this study practically suggests that marketers and network managers need to use differentiated communication strategies for twitters as a marketing strategic option.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.2
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• pp.505-513
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• 2017

In this study, we collected 200,578,703 geo-tweets and removed the twitter bots. Using the concept of activity radius, Twitter users are classified. Users are also divided first into domestic and overseas, and again domestic ones are divided into locals and non-locals. Statistical characteristics of activity strength and active area of Twitter users are described according to activity radius and home region, and the geographical distribution is presented visually. Through a case study of Las Vegas, we have identified the difference in activity strength and active area by the user's home residence. We expect to derive theories about human mobility by analyzing various cities with the method proposed in this study.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.8
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• pp.301-308
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• 2015

SNS is a web-based online platform service supporting the formation of relations between users. SNS users have usually used a desktop or laptop for this purpose so far. However, the number of SNS users is greatly increasing and their access to the web is improving with the spread of smart phones. They share their daily lives with other users through SNSs. We can detect events if we analyze the contents that are left by SNS users, where the individual acts as a sensor. Such analyses have already been attempted by many researchers. In particular, Twitter is used in related spheres in various ways, because it has structural characteristics suitable for detecting events. However, there is a limitation concerning the detection of events and their locations. Thus, we developed a system that can detect the location immediately based on the district mentioned in Twitter. We tested whether the system can function in real time and evaluated its ability to detect events that occurred in reality. We also tried to improve its detection efficiency by removing noise.

• The Journal of the Korea Contents Association
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• v.14 no.1
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• pp.139-149
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• 2014

This study attempts to explore the inter-media agenda setting effect between television and Twitter based on the framework of the two-step flow theory. Twitter's increasingly important role in political communication can be effectively addressed by examining the process by which Twitter users form their opinions on television debate program. Content analyses of Twitter discussions after television debate of the Korean presidential candidates provided interesting insights into how Twitter's opinion leaders reflect on the televised debates. The results show that Twitter mentions rather focus on personality traits of the candidates while television debates emphasize the candiates' policy issues. Specifically, Twitter users mainly concentrated on the political ideology and morality of the candidates. In sum, Twitter seems to have its own way of influencing the public opinion separately from the television.

• Journal of the Korea Convergence Society
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• v.9 no.12
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• pp.39-45
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• 2018

Twitter users use 'Following', 'Retweet' and so on to find tweets that they are interested in. However, it is difficult for users to find tweets that are of interest to them on Twitter, which has more than 300 million users. In this paper, we developed a customized tweet recommendation system to resolve it. First, we gather current trends to collect tweets that are worth recommending to users and popular tweets that talk about trends. Later, to analyze users and recommend customized tweets, the users' tweets and the collected tweets are categorized. Finally, using Web service, we recommend tweets that match with user categorization and users whose interests match. Consequentially, we recommended 67.2% of proper tweet.

• Asian Journal for Public Opinion Research
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• v.6 no.1
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• pp.31-38
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• 2018

Leading up to the 2019 presidential election in Indonesia, campaigns have emerged through social media, particularly Twitter, using various hashtags, such as #2019GantiPresiden (2019 Change President) and #TetapJokowi (Always Jokowi). This paper tries to understand the presidential candidates' power map in forming opinions and influencing voter behavior by analyzing Twitter from August 6, 2018 to September 15, 2018, just before the beginning of the official campaign period, by searching for the keyword "pemilihan presiden RI Tahun 2019" (RI presidential election in 2019). According to our NodeXL's analysis, there were 1,650 active Twitter users talking about the 2019 presidential election. The 1,650 Twitter users have formed a communication network of 46,750 relationships formed from messages in the form of tweets, comments, and retweets. Our analysis found that those mentioning "pilihan presiden 2019" form large communication networks around four clusters: one for each of the two candidates (Jokowi and Prabowo) and two for opinion leaders who are undecided about the election (Gus Mus and Mas Piyu). GusMus is a religious leader, as an official of the PBNU Rais Syuriah (an Islamic organization) and has a large following both on and off Twitter. "MasPiyu" is an unidentified Twitter user; he only has a large following on Twitter, but does not have support offline.

• International Journal of Contents
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• v.8 no.4
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• pp.50-55
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• 2012

This study compared cross-national Twitter use between Korea and Japan. The main exploratory variables were a) cultural traits and b) disclosure of geographic information. Twitter use was measured by the degree of reciprocity and the numbers of Tweets, followings, and followers. Data were collected using API-based software and analyzed with independent samples t-tests. Content analysis was conducted to validate the findings. The results indicate that Korean and Japanese users employ their own communication strategies reflecting their cultural orientation.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.6
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• pp.7-13
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• 2014

Twitter is a microblogging service that allows users to post short messages on a variety of topics in real-time. In this work, we analyze Twitter messages posted during the 2012 elections and find those implications. This study uses Twitter messages related to the 2012 South Korean presidential campaign. The three main candidates are represented by the abbreviations A, M, and P. According to the statistical analysis, the number of tweets and re-tweets for candidate P was relatively stable over the entire campaign period. Candidate P had the highest percentage of terms related to elections pledges, and candidates A and M were judged to be a little bit poorer with respect to campaign promises. The positive terms ratio for candidate P was higher than those for the other two candidates. The negative terms ratio in the Twitter messages of P was considerably smaller than those of candidates A and M. After considering all these results, it is suggested cautiously that Twitter messages posted during an election campaign could be correlated with the outcome of the election.

• Journal of Multimedia Information System
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• v.2 no.3
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• pp.287-294
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• 2015

We are living in epoch of information when Internet touches all aspects of our lives. Therefore, it provides a plenty of services each of which benefits people in different ways. Electronic Mail (E-mail), File Transfer Protocol (FTP), Voice/Video Communication, Search Engines are bright examples of Internet services. Between them Social Network Services (SNS) continuously gain its popularity over the past years. Most popular SNSs like Facebook, Weibo and Twitter generate millions of data every minute. Twitter is one of SNS which allows its users post short instant messages. They, 100 million, posted 340 million tweets per day (2012)[1]. Often big amount of data contains lots of noisy data which can be defined as uninteresting and unclassifiable data. However, researchers can take advantage of such huge information in order to analyze and extract meaningful and interesting features. The way to collect SNS data as well as tweets is handled by crawlers. Twitter crawler has recently emerged as a great tool to crawl Twitter data as well as tweets. In this project, we develop Twitter Crawler system which enables us to extract Twitter data. We implemented our system in Java language along with MySQL. We use Twitter4J which is a java library for communicating with Twitter API. The application, first, connects to Twitter API, then retrieves tweets, and stores them into database. We also develop crawling strategies to efficiently extract tweets in terms of time and amount.