• International Journal of Contents
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• 제13권1호
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• pp.31-37
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• 2017

Using the network analysis method, this study investigates the communication structure of Open Data on the Twitter sphere. It addresses the communication path by mapping influential activities and comparing the contents of tweets about Open Data. In the years 2015 and 2016, the NodeXL software was applied to collect tweets from the Twitter network, containing the term "opendata". The structural patterns of social media communication were analyzed through several network characteristics. The results indicate that the most common activities on the Twitter network are related to the subjects such as new applications and new technologies in Open Data. The study is the first to focus on the structural and informational pattern of Open Data based on social network analysis and content analysis. It will help researchers, activists, and policy-makers to come up with a major realization of the pattern of Open Data through Twitter.

• 한국감성과학회:학술대회논문집
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• 한국감성과학회 2011년도 추계학술대회
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• pp.52-53
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• 2011

• Journal of Contemporary Eastern Asia
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• 제20권2호
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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.

• International Journal of Advanced Culture Technology
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• 제9권2호
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• pp.80-85
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• 2021

This study is to analyze the structure of the networks of tourism marketing on Twitter, identifying the most prominent users, the flow of information about tourism marketing, and the interaction between the users posting tweets. This study employs NodeXL pro as a visualization software package for social network analysis. The number of vertices or nodes is 171, and the number of the unique edges or links is 128, but there are 101 edges with duplicates, so the total links are 229, which means that there are fewer Twitter accounts in the social network on tourism marketing, but they have a few close relationships by sharing information. The research can map the social network of communicators of tourism marketing using Twitter data. The network has a complicated pattern, including one independent network and some connected networks. Some mediators connect each network and can control the information flow of tourism marketing. More communicators are getting the information than the ones providing it, which means that there is likely to be the dependence of information among communicators that can cause an obstacle and distortion of the information flow system, especially in the independent network.

• International Journal of Computer Science & Network Security
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• 제21권1호
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• pp.97-106
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• 2021

Social networking platforms have become a smart way for people to interact and meet on internet. It provides a way to keep in touch with friends, families, colleagues, business partners, and many more. Among the various social networking sites, Twitter is one of the fastest-growing sites where users can read the news, share ideas, discuss issues etc. Due to its vast popularity, the accounts of legitimate users are vulnerable to the large number of threats. Spam and Malware are some of the most affecting threats found on Twitter. Therefore, in order to enjoy seamless services it is required to secure Twitter against malicious users by fixing them in advance. Various researches have used many Machine Learning (ML) based approaches to detect spammers on Twitter. This research aims to devise a secure system based on Hybrid Similarity Cosine and Soft Cosine measured in combination with Genetic Algorithm (GA) and Artificial Neural Network (ANN) to secure Twitter network against spammers. The similarity among tweets is determined using Cosine with Soft Cosine which has been applied on the Twitter dataset. GA has been utilized to enhance training with minimum training error by selecting the best suitable features according to the designed fitness function. The tweets have been classified as spammer and non-spammer based on ANN structure along with the voting rule. The True Positive Rate (TPR), False Positive Rate (FPR) and Classification Accuracy are considered as the evaluation parameter to evaluate the performance of system designed in this research. The simulation results reveals that our proposed model outperform the existing state-of-arts.

• 패션비즈니스
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• 제15권1호
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• pp.158-170
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• 2011

The purpose of this study was to examine how recently fashion corporate did use SNS applications for their product promotion strategies as case studies, and to provide what kinds of SNS marketing strategies would be developed for fashion corporate. Specifically, this study was focused on Twitter among SNS applications. For this study, Internet webs, news paper, articles, and other press work were used for resources. Five fashion corporate such as Buckaroo, MLB, North Faces, Kolon, and ABC Mart were analyzed. As the results, first, fashion corporate used Twitter as the marketing tool for their product promotion. Second, they tried to make an increase the numbers of Twitter follower from their customers. Third, Twitter was used for making higher customer loyalty by fashion corporate through a variety of program such as special events, game, music, or viral marketing. However, there were still some limitations on fashion corporate's Twitter usage, compared to other non-fashion corporate. Thus, fashion corporate needs to provide more creative and unique Twitter marketing strategies. Therefore, based on these results, fashion brand merchandising marketing strategies of fashion products would be provided from this study.

• 경영정보학연구
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• 제14권1호
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• pp.21-35
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• 2012

최근 트위터와 페이스북 등의 소셜 네트워크 서비스 (SNS)가 전세계적으로 급성장하고 있다. 특히 트위터는 팔로잉이나 리트윗 기능 등을 이용한 정보의 확산이 용이하므로, 새로운 홍보 마케팅 수단으로 각광받고 있다. 본 연구에서는 기업 트위터 이용자를 상호작용 형태별로 분류해서 그룹별 영향력 정도와 프로파일을 분석하고, 트위터의 콘텐츠를 속성별로 분류해서 확산 정도와 내용을 심층적으로 분석함으로써, 효과적인 기업 홍보 마케팅용 트위터 활용 방안을 제안하였다. 국내 대표 IT 기업인 K사의 홍보 마케팅용 트위터 계정을 구독하고 있는 약 2,800여명의 팔로어들을 대상으로 연구를 진행한 결과, 기업 트위터 이용자들은 구독 콘텐츠의 확산에 다소 소극적인 것을 알 수 있었다. 또한 리트윗에 참여하는 확산 그룹과 비구독 확산 그룹의 특성을 분석한 결과, 10,000명 이상의 많은 팔로어를 보유한 이 용자보다는 1,000명 이하의 작은 네트워크를 가진 이용자들의 확산 기여도가 높았다. 트위터 콘텐츠의 속성별로 발행 건수 대비 리트윗 되는 비율을 분석한 결과에서는 채용, 이벤트, IT 정보, 일반홍보의 순서로 높게 나타났다. 결론에서는 연구 결과에 기반한 실무적인 제언이 심층적으로 논의 되었다.

• Journal of Contemporary Eastern Asia
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• 제12권1호
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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 and communication convergence engineering
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• 제10권2호
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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.

• 정보과학회 논문지
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• 제41권10호
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• pp.785-791
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• 2014

트위터는 페이스북과 더불어 전 세계적으로 인기 있는 SNS(Social Network Service)이다. 트위터에서 이메일 인증 방식을 악용하여 대량 생성된 스패머 계정은 유해한 콘텐츠로 트위터 사용자들에게 불편함을 준다. 본 논문에서는 이러한 문제를 해결하고자 관계 기반 특징을 이용한 스패머 탐지 기법을 제안한다. 관계 기반 특징이란 사용자의 호감 정도를 표현할 수 있는 친구 관계 특징과 사용자 간의 유사성을 나타낼 수 있는 유형 관계 특징들을 의미한다. 기존의 스패머 탐지 기법과 본 논문에서 제안하는 탐지 기법의 성능을 스패머의 비율을 3%에서 30%까지 변화시키면서 비교 실험한 결과, 본 논문에서 제안하는 기법이 Naive Bayesian Classifier와 Decision Tree 모두에서 더 우수한 성능을 보였다.