• Title/Summary/Keyword: 마이크로 블로깅 서비스

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A case study on using micro-blogging in library information services - Focuses on twitter (마이크로 블로깅을 활용한 도서관 정보서비스 사례 분석 - 트위터를 중심으로)

  • Kim, Ye-Rin;Jung, Young-Mi
    • Proceedings of the Korean Society for Information Management Conference
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    • 2010.08a
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    • pp.81-88
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    • 2010
  • 오늘날과 같은 정보통신 발달의 시대에서 정보 전달의 신속성과 접근성을 보장하는 것은 정보서비스 기관의 경쟁력 강화에 매우 중요한 일이다. 마이크로 블로깅을 제공하는 서비스 중 하나인 트위터는 web 2.0 서비스의 대표주자로 시 공간을 초월한 도서관 정보서비스의 신속성과 접근성을 지원하는 강력한 도구로 부상하고 있다. 이에 본 연구에서는 국내외 도서관의 트위터를 중심으로 마이크로 블로깅을 활용한 정보서비스 적용사례를 조사하고 이와 같은 신기술 적용 활성화를 위한 시사점을 제시하고자 한다. 본 연구에서 조사한 사례는 미국 의회도서관, 미국 뉴욕 공공도서관, 영국 국립 도서관, 국내의 국립중앙도서관 디브러리, 포항공대 도서관인 포스텍 도서관 이고 주요하게 트위터의 수치적인 현황, 활용 목적, 내용, 이용하는 인터페이스 측면들을 조사 분석하였다.

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Profiling Usage Motivation in Micro-blogging Service by Q-methodology : The case of me2DAY (Q 방법론을 적용한 마이크로 블로깅 서비스의 이용 동기 유형 분석 : 미투데이 사례)

  • Kim, Kyung-Kyu;Kim, Hyo-Jin;Ryoo, Sung-Yul
    • The Journal of Society for e-Business Studies
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    • v.15 no.3
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    • pp.45-61
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    • 2010
  • This study investigated the types of intention to use micro-blogging service. In this study, we classified micro-blogging users' motivations using Q methodology which enables measure objectivity with subjective activity like individual thinking and feeling. The results of this study showed that micro-blogging service users' motivationswere classified into four types. Type 1 is 'relationship oriented type' and Type 2 is 'self-expression type.' Type 3 is 'time consumption type' and Type 4 is 'information seeking type.' The findings imply that the characteristics of each user type can be utilized to customize micro-blogging services.

An Auto-blogging System based Context Model for Micro-blogging Service (마이크로 블로깅 서비스를 지원하기 위한 컨텍스트 모델 기반 자동 블로깅 시스템)

  • Park, Jae-Min;Lee, Sang-Yong
    • Journal of Digital Convergence
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    • v.10 no.4
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    • pp.341-346
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    • 2012
  • Social network service is service that enables the human network to be built up on web. It is important to record users' information simply and establish the network with people based on the information to provide with the social network service effectively. But it is very troublesome work for the user to input his or her own information on the mobile environment. In this paper we suggested a system which classifies users' behavior using context and creates blogging sentences automatically after inferring the destination. For this, users' behavior is classified and the destination is inferred with the sequence matching method using Naive Bayes classification. Then sentences which are suitable for situation is created by arranging the processed context using the structure of 5W1H. The system was evaluated satisfaction degree by comparing the created sentences based on actually collected data with users' intension and got accuracy rate of 88.73%.

Analyzing the Effectiveness of Discussion Learning using the Technology Acceptance Model on Social Networking Service (기술수용모형을 이용한 소셜 네트워킹 기반 토의 학습의 효과 분석)

  • Kim, Soo-Hwan;Han, Seon-Kwan
    • Journal of The Korean Association of Information Education
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    • v.15 no.4
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    • pp.571-578
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    • 2011
  • In this study, we suggested a strategy about a discussion class using Twitter, and experimented it inside an elementary school classroom. Elementary students participated in a panel discussion and the others discussed as audience using Twitter. After the discussion, we investigated the effectiveness of our strategy using the Technology Acceptance Model and verified students' satisfaction and ability to collaborate through giving them a questionnaire. As a result, the perceived ease of use positively effected the perceived usefulness and the perceived usefulness influenced the attitude and the attitude affect on intention to use. Also, students were satisfied with the discussion class on Twitter and had a positive perception about collaboration with it. As a result of regression, perception of collaboration among the students influenced the perceived usefulness positively. The results in this study show the effectiveness of using the discussion class strategy on Twitter.

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SHRT : New Method of URL Shortening including Relative Word of Target URL (SHRT : 유사 단어를 활용한 URL 단축 기법)

  • Yoon, Soojin;Park, Jeongeun;Choi, Changkuk;Kim, Seungjoo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.38B no.6
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    • pp.473-484
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    • 2013
  • Shorten URL service is the method of using short URL instead of long URL, it redirect short url to long URL. While the users of microblog increased rapidly, as the creating and usage of shorten URL is convenient, shorten url became common under the limited length of writing on microblog. E-mail, SMS and books use shorten URL well, because of its simplicity. But, there is no relativeness between the most of shorten URLs and their target URLs, user can not expect the target URL. To cover this problem, there is attempts such as changing the shorten URL service name, inserting the information of website into shorten URL, and the usage of shortcode of physical address. However, each ones has the limits, so these are the trouble of automation, relatively long address, and the narrowness of applicable targets. SHRT is complementary to the attempts, as getting the idea from the writing system of Arabic. Though the writing system of Arabic has no vowel alphabet, Arabs have no difficult to understand their writing. This paper proposes SHRT, new method of URL Shortening. SHRT makes user guess the target URL using Relative word of the lowest domain of target URL without vowels.

Preliminary Research for Korean Twitter User Analysis Focusing on Extreme Heavy User's Twitter Log (국내 트위터 유저 분석을 위한 예비연구 )

  • Jung, Hye-Lan;Ji, Sook-Young;Lee, Joong-Seek
    • Journal of the HCI Society of Korea
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    • v.5 no.1
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    • pp.37-43
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    • 2010
  • Twitter has been continuously growing since October, 2006. Especially, not only the users and the number of messages have been increasing but also a new concept in social networking called 'micro blogging' has diffused. Within Korea, service such as 'me2day' has already been introduced and the improvement of internet accessibility within mobile devices is expected to expand the 'micro blogs'. In this point, this research is executed to study the new medium, 'micro blog'. To do so, we collected and analyzed Twitter logs of Korean users. Especially, we were curious about the extreme heavy users using Twitter, despite of the linguistic and cultural barrier of the foreign service. Who they are, why and how they use the 'micro blog'. First, we reviewed the general aspect of followers and messages by collecting a certain number of random samples. Using the Lorenz curve we found out that there was the imbalance within the users and based on this phenomenon we deducted an extreme heavy user group. In order to perform further analysis, log analysis was performed on the extreme heavy users. As the result, the users used multiple mobile and desktop 'Twitter' clients. The usage pattern was similar to that of internet usage time but was used during their "micro" time. The users using 'Twitter' not only to spread messages about important information, special events and emotions, but also as a habitual 'chatting tool' to express ordinary personal chats similar to SMS and IM services. In this research, it is proved that 68% of the total messages were ordinary personal chats. Also, with 24% of the total messages were retweets, we were able to find out that virtually connected 'people' and 'relationships' acted as the dominant trigger of their articulation.

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Tweets analysis using a Dynamic Topic Modeling : Focusing on the 2019 Koreas-US DMZ Summit (트윗의 타임 시퀀스를 활용한 DTM 분석 : 2019 남북미정상회동 이벤트를 중심으로)

  • Ko, EunJi;Choi, SunYoung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.2
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    • pp.308-313
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    • 2021
  • In this study, tweets about the 2019 Koreas-US DMZ Summit were collected along with a time sequence and analyzed by a sequential topic modeling method, Dynamic Topic Modeling(DTM). In microblogging services such as Twitter, unstructured data that mixes news and an opinion about a single event occurs at the same time on a large scale, and information and reactions are produced in the same message format. Therefore, to grasp a topic trend, the contextual meaning can be found only by performing pattern analysis reflecting the characteristics of sequential data. As a result of calculating the DTM after obtaining the topic coherence score and evaluating the Latent Dirichlet Allocation(LDA), 30 topics related to news reports and opinions were derived, and the probability of occurrence of each topic and keywords were dynamically evolving. In conclusion, the study found that DTM is a suitable model for analyzing the trend of integrated topics in a specific event over time.