• 한국HCI학회:학술대회논문집
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• 2006.02b
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• pp.435-441
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• 2006

블로그는 사이버 공간에서 자신을 표현할 수 있는 효과적인 도구로 사용되고 있으며 그 개방적인 특성으로 인해 다른 사람들과 교류할 수 있는 기회를 증대시켰다. 따라서 블로그는 사이버 상에서 사람들이 특정한 인상을 만들어 내고 그것을 받아들이는 과정이 활발히 일어나는 공간이라 할 수 있다. 본 연구는 블로그 사용자들을 대상으로 한 심층 인터뷰를 통하여 사이버 인상 형성에 영향을 주는 구체적인 표현 요소와 의도한 인상과 지각된 인상과의 관계에 대하여 분석하였다. 사람들은 사이버 공간에서 긍정적인 자신의 모습을 만들고자 하며 의도하는 인상 차원에 따라 사용하는 표현요소에서 차이를 보였다. 또한 직접적으로 의도하지 않은 표현 요소가 인상을 지각하는데 있어 영향을 주고 있다는 사실을 확인하였다.

• Knowledge Management Research
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• v.19 no.1
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• pp.133-146
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• 2018

This study develops an Education framework for users who need public open data for workplace etiquette education in a timely manner by mobile application. It facilitates utilizing efficiently Workplace etiquette contents that scattered in various platforms such as blogs, Youtube and web-sites run by private education agencies. Furthermore, it makes Public open data for workplace etiquette through gathering 'metadata', which is a comprehensive source of workplace etiquette. Accordingly, framework changes recognition about necessity of workplace etiquette education positively and suggests method that can promote effective workplace etiquette education. If the system in the study can provide public open data of workplace etiquette education, many young job applicants and workers will have a proper perception on it and sound workplace etiquette culture will be settled in the companies. Public data has been rising as a vital national strategic asset these days. Hopefully the public data will pave a way to discover the blue ocean in the market and open up a new type of businesses.

• Proceedings of the Korea Database Society Conference
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• 2008.05a
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• pp.405-412
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• 2008

It is certain that knowledge sharing is critical phenomenon to be concerned in web 2.0 days. Today, people can learn anything they want to know such as recipes or even with regard to the knowledge in the specific field through internet. In this trend, blog has settled down to the major part of Web 2.0 culture. There are various kinds of activities through blog vigorously. Still, people can not recognize how important information they upload is, i.e., they should take the responsibilities for information so that it can be more clear, exact and trust-building.

• Journal of Information Science Theory and Practice
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• v.2 no.4
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• pp.49-60
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• 2014

The present discourse lasts around, information pollution, causes and concerns of information pollution, internet as a major causality and how it affects the decision making ability of an individual. As, information producers in the process to not to lose the readership of their content, and to cater the information requirements of both the electronic and the print readers, reproduce almost the whole of the printed information in digital form as well. Abundant literature is also equally produced in electronic format only, thereon, sharing this information on hundreds of social networking sites, like, Facebook, Twitter, Blogs, Flicker, Digg, LinkedIn, etc. without attributions to original authors, have created almost a mess of this whole information produced and disseminated. Accordingly, the study discusses about the sources of information pollution, the aspects of unstructured information along with plagiarism. Towards the end of the paper stress has been laid on information literacy, as how it can prove handy in addressing the issue with some measures, which can help in regulating the behaviour of information producers.

• Journal of the Korean Data and Information Science Society
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• v.25 no.3
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• pp.665-676
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• 2014

As social media draws attention as a business tool, organizations, large or small, are trying to exploit social media in their business. However, lack of understanding the characteristics of each social media led them to develop a naive strategy for dealing with social media. Thus, this study aims to deepen the understanding by comparatively analyzing how social media users perceive (the image of) each social media. Facebook, Twitter, YouTube, Blogs, Communities and Cyworld were chosen for our study and data from 132 respondents were analyzed using multidimensional scaling technique. The results show that there are meaningful differences in users' perception of social media attributes, which are grouped into four; information feature, motivation, promotion tool, usability. It is also analyzed whether such differences can be found between male and female users. (Such differences are also analyzed in both male and female users' perceptions.) Further, we discuss some implications of the research results for both practitioners and researchers.

• Journal of Information Processing Systems
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• v.14 no.4
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• pp.904-915
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• 2018

We demonstrate how social media content can be used to predict the unemployment rate, a real-world indicator. We present a novel method for predicting the unemployment rate using social media analysis based on natural language processing and statistical modeling. The system collects social media contents including news articles, blogs, and tweets written in Korean, and then extracts data for modeling using part-of-speech tagging and sentiment analysis techniques. The autoregressive integrated moving average with exogenous variables (ARIMAX) and autoregressive with exogenous variables (ARX) models for unemployment rate prediction are fit using the analyzed data. The proposed method quantifies the social moods expressed in social media contents, whereas the existing methods simply present social tendencies. Our model derived a 27.9% improvement in error reduction compared to a Google Index-based model in the mean absolute percentage error metric.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.415-424
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• 2005

The rapid growth of blog has caused information overload where bloggers in the virtual community space are no longer able to effectively choose the blogs they are exposed to. Recommender systems have been widely advocated as a way of coping with the problem of information overload in e-business environment. Collaborative Filtering (CF) is the most successful recommendation method to date and used in many of the recommender systems. Therefore, we propose a CF-based recommender system for bloggers in the virtual community space. Our proposed methodology consists of three main phases: In the first phase, we apply the "Interest Value" to a recommender system. The Interest Value is a quantity value about user preference in virtual community, and can measure the opinion of users accurately. Next phase, we generate the neighborhood group based on the Interest Value. In the final phase, we use the Community Likeness Score (CLS) to generate the top-n recommendation list. The methodology is explained step by step with an illustrative example and is verified with real data of a blog service provider.

• Journal of the Korea Society of Computer and Information
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• v.23 no.9
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• pp.27-34
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• 2018

Personal media centered on blogs, Twitter, and Facebook has opened up a personal broadcasting area while meeting platforms such as YouTube and Africa TV. Due to the many advantages and disadvantages of personal broadcasting, a study on it was necessary and statistical survey was conducted. The study conducted opinion survey of 118 university students on personal broadcasting. As a result, we are getting news using smartphones and mainly watching videos through YouTube, and watching videos type in the order of games, music videos and sports. Satisfaction rate of video was 72.4%, 80.2% of survey did not use paid services, experiences about personal broadcasting was 96.6% and 90.5% of survey the prospect of person broadcasting of the opinion that "it will be expanded". The first thing we want to be improved in personal broadcasting is the prevention of abusive language and hate speech. Second, we were reluctant to sensational content. Third, the survey results are the improvement of excessive advertising.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.1057-1060
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• 2013

블로그가 1인미디어로서 영향력을 행사하고 있으며 기업과 함께 마케팅과 광고가 진행되고 있을 정도로 산업적으로 다양하게 사용되고 있으나 블로그에 대한 평가는 대부분 정성적으로 행해지고 있다. 하지만 수십 수백만 개의 블로그를 수작업으로 확인하는 것은 쉬운 일이 아니며 자동화된 정량적인 평가가 시급한 실정이다. 본 논문에서는 블로그의 구조적인 특성을 이용한 평가방법을 제안하고 포털사이트 네이버에서 매년 발표되는 파워블로그 중 요리, 육아, 미술/디자인 카테고리의 파워블로그를 비교하여 성능을 평가한다. 평가의 방법은 일반적인 미디어 파워의 평가방법인 구독자수를 비교하였으며 본 논문에서 제시하고 있는 평가의 방법을 통해서 얻어진 블로그가 높은 수의 구독자를 가지고 있음이 판명되어 정성적인 평가 보다 높은 성능을 보임을 알 수 있었다.

• International Journal of Advanced Culture Technology
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• v.11 no.3
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• pp.190-198
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• 2023

Sentiment analysis can be applied to all texts generated from websites, blogs, messengers, etc. The study fulfills an artificial intelligence sentiment analysis estimating visiting evaluation opinions (reviews) and visitor ratings, and suggests a deep learning model which foretells either an affirmative or a negative inclination for new reviews. This study operates review big data about Jeju tourist attractions which are extracted from Google from October 1st, 2021 to November 30th, 2021. The normalization data used in the propensity prediction modeling of this study were divided into training data and test data at a 7.5:2.5 ratio, and the CNN classification neural network was used for learning. The predictive model of the research indicates an accuracy of approximately 84.72%, which shows that it can upgrade performance in the future as evaluating its error rate and learning precision.