• Journal of Digital Convergence
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• v.9 no.3
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• pp.95-104
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• 2011

This study explored how political figures build their image using twitters. To examine the research question, this study analyzed twitter messages in five political figures: Si-Min, Yu, Jung-hee, Lee, Mun-soo, Kim, and Young-gil, Song. The findings showed that except for Mrs. Lee, the other political figures presented more one-way messages than two-way messages in twitters. Even though twitter has benefits of communicating instantly and two-way communication between followers and followings, most messages in their twitters were limited to informative message. The study also classified the messages into social-oriented and individual-oriented in each politician' s twitter. The result presented that Mrs. Lee twitter included individual-oriented messages, but the other three political figures had more social-oriented messages.

• Journal of Convergence for Information Technology
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• v.9 no.11
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• pp.81-91
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• 2019

Recently, social network service (SNS) is actively used by public. Among them, Twitter has a lot of tweets including sentiment and it is convenient to collect data through open Aplication Programming Interface (API). In this paper, we analyze social issues and suggest the possibility of using them in marketing through sentimental information of users. In this paper, we collect twitter text about social issues and classify as positive or negative by sentiment classifier to provide qualitative analysis. We provide a quantitative analysis by analyzing the correlation between the number of like and retweet of each tweet. As a result of the qualitative analysis, we suggest solutions to attract the interest of the public or consumers. As a result of the quantitative analysis, we conclude that the positive tweet should be brief to attract the users' attention on the Twitter. As future work, we will continue to analyze various social issues.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.3
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• pp.879-886
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• 2018

The basic search engine on Twitter shows not only tweets that contain search keywords, but also all articles written by users with nicknames containing search keywords. Since the tweets unrelated to the search keyword are exposed as search results, it is inconvenient to many users who want to search only tweets that include the keyword. To solve this inconvenience, this study improved the search function of Twitter by developing an algorithm that searches only tweets that contain search keywords. The improved functionality is implemented as a Web service using ASP.NET MVC5 and is available to many users. We used a powerful collection method in C# to retrieve the results of an object, and it was also possible to output them according to the number of 'retweets' or 'favorites'. If the number of retrieved numbers is less than a given number, we also added an exclusion filter function. Thus, sorting search results by the number of retweets or favorites, user can quickly search for opinions that are of interest to many users. It is expected that many users and data analysts will find the developed function convenient to search on Twitter.

• 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.

• 한국어정보학회:학술대회논문집
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• 2016.10a
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• pp.305-306
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• 2016

식품안전 사고가 발생했을 때 뉴스, 인터넷 기사를 통해 정보를 인지하기 전에 그 음식을 섭취하는 경우가 발생하는 문제점 최소화하기 위하여 실시간 트윗 분석으로 현재 발생한 식품안전 키워드와 어느 지역에서 발생했는지를 신속하게 파악하고, 키워드 연관관계 분석 프로그램을 활용하여 정확한 정보를 추출한다. 이와 더불어, SNS 등 다양한 정보 소스로부터 추출한 정보를 간단명료하게 파악하기 위해서 워드 클라우드 등 데이터 시각화 기법을 활용하여 시각화로 정보를 제공한다. 이 기법은 식품안전 뿐만 아니라 최근 발생한 콜레라 감염 발생과 같은 문제를 해결하기 위한 방법으로 활용될 수 있을 것이다.

• Annual Conference on Human and Language Technology
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• 2016.10a
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• pp.305-306
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• 2016

식품안전 사고가 발생했을 때 뉴스, 인터넷 기사를 통해 정보를 인지하기 전에 그 음식을 섭취하는 경우가 발생하는 문제점 최소화하기 위하여 실시간 트윗 분석으로 현재 발생한 식품안전 키워드와 어느 지역에서 발생했는지를 신속하게 파악하고, 키워드 연관관계 분석 프로그램을 활용하여 정확한 정보를 추출한다. 이와 더불어, SNS 등 다양한 정보 소스로부터 추출한 정보를 간단명료하게 파악하기 위해서 워드 클라우드 등 데이터 시각화 기법을 활용하여 시각화로 정보를 제공한다. 이 기법은 식품안전 뿐만 아니라 최근 발생한 콜레라 감염 발생과 같은 문제를 해결하기 위한 방법으로 활용될 수 있을 것이다.

• Smart Media Journal
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• v.1 no.4
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• pp.72-78
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• 2012

SNS supports the formation of relationships between users in common interests and provides services allowing for clique management, sharing contents, and so on. It also has common functions such as acting as primary platforms smoothing the sharing and distribution by combination with various contents. Hence, questionnaire has been conducted to users of all of Twitter, Facebook and KakaoStory, and the factors affected by each service are presented by statistical analyses of the survey and the results are resolved by dividing them into complete and instrumental social capital. This study will be able to provide a standard for users to select SNS according to their purposes and contribute to development of new SNS or improvement of existing ones.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.6
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• pp.1471-1477
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• 2012

Social Network has common functions such as acting as primary platforms smoothing the sharing and distribution by combination with various contents. Hence, questionnaire has been conducted to users of all of Twitter, Facebook and KakaoStory, and the factors affected by each service are presented by statistical analyses of the survey and the results are resolved by dividing them into complete and instrumental social capital. This study will be able to provide a standard for users to select Social Network according to their purposes and contribute to development of new Social Network or improvement of existing ones.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.1452-1454
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• 2013

최근 스마트 기기와 SNS가 대중화가 되면서, 이를 기반으로 사용자의 감정 분석을 통한 추천 연구가 활발하게 진행되어 지고 있다. 본 논문에서는 감정표현단어 500여개와 이모티콘을 활용하여 감정 범주를 9가지로 분류하고, 트위터광장의 여러 유명인사 트위터 타임라인의 텍스트를 가져온 후, 감정상태 분석으로 감정 범주를 카운트 한다. 이를 통해, 한사람의 감정상태의 수치를 나타내고, 추후 음악, 음식, 문화 활동 등을 다양하게 추천할 수 있는 감정상태분석모듈을 설계 및 구현한다.

• Journal of Korean Society of societal Security
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• v.2 no.3
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• pp.16-18
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• 2009