• Journal of Korea Multimedia Society
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• v.13 no.8
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• pp.1245-1255
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• 2010

In current Web 2.0 environment, one of the most core technology is social bookmarking which users put tags and bookmarks to their interesting Web pages. The main purpose of social bookmarking is an effective information service by use of retrieval, grouping and share based on user's bookmark information and tagging result of their interesting Web pages. But, current social bookmarking system uses the number of bookmarks and tag information separately in information retrieval, where the number of bookmarks stand for user's degree of interest on Web contents, information retrieval, and classification serve the purpose of tag information. Because of above reason, social bookmarking system does not utilize effectively the bookmark information and tagging result. This paper proposes a Web contents ranking algorithm combining bookmarks and tag information, based on preceding research on associative tag extraction by tag clustering. Moreover, we conduct a performance evaluation comparing with existing retrieval methodology for efficiency analysis of our proposed algorithm. As the result, social bookmarking system utilizing bookmark with tag, key point of our research, deduces a effective retrieval results compare with existing systems.

• Journal of Korea Multimedia Society
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• v.14 no.4
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• pp.567-576
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• 2011

In current Web 2.0 environment, one of the most core technology is social bookmarking which users put tags and bookmarks to their interesting Web pages. The main purpose of social bookmarking is an effective information service by use of retrieval, grouping and share based on user's bookmark information and tagging result of their interesting Web pages. But, current social bookmarking system uses the number of bookmarks and tag information separately in information retrieval, where the number of bookmarks stand for user's degree of interest on Web contents, information retrieval, and classification serve the purpose of tag information. Because of above reason, social bookmarking system does not utilize effectively the bookmark information and tagging result. This paper proposes a Web contents ranking algorithm combining bookmarks and tag information, based on preceding research on associative tag extraction by tag clustering. Moreover, we conduct a performance evaluation comparing with existing retrieval methodology for efficiency analysis of our proposed algorithm. As the result, social bookmarking system utilizing bookmark with tag, key point of our research, deduces a effective retrieval results compare with existing systems.

• 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.

• Journal of the Korean Society for information Management
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• v.27 no.1
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• pp.41-60
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• 2010

This study aims to analyze the properties of the tags used in the fiction genre, the structural aspect of the patterns and the contents of the tags by utilizing LibraryThing, where the tags are assigned in work units of FRBR. A comparative analysis was conducted in terms of the level of association between the descriptive terms in bibliography and LCSH terms. The study also examined the sources of the tags not included in the bibliographic descriptions or LCSHs, what aspects of work they represented, and the terms used as tags in relation to the work. By restricting the study to a single genre, a number of tags that reflected the characteristics of fiction (three elements of the fiction which are theme, plot, style and three elements of the fiction composition which are character, event, setting) were extracted. This study finds out the role of the tag making up the taxonomy and proposes a new direction for the tagging system by demonstrating the possibility of using tags as facets in information organization and retrieval.

• Journal of the Korean Society for Library and Information Science
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• v.42 no.4
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• pp.463-480
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• 2008

This study was to review the possible characteristics and patterns that occur when comparing control language constructing guidelines, by analyzing the formal characteristics of folksonomy tags in university libraries. Based on subjected tags at university libraries for a period of 6 months the structure and form of folksonomy was examined. The object tags were analyzed based on the thesaurus development guidelines. The results for this research will provide baseline data for the use of folksonomy tag applications in digital libraries.

• Journal of Contemporary Eastern Asia
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• v.19 no.1
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• pp.123-143
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• 2020

This study examines the interplay between the reactions of YouTube users and North Korean propaganda. Interesting enough, the study has noticed changes in the strict media environment under young leader Kim. Messages delivered by the communist regime to the outside world appeared to resemble those of 'normal' countries. Although North Korean YouTube was led mainly by the account operator, visitors from different nations do comment on the channel, which suggests the possibility of building international communities for propaganda purposes. Overall, the study observed a sparsely connected social network among ordinary commenters. However, the operator did not exercise tight control over peer-to-peer communication but merely answered questions and tried to facilitate mass participation. In contrast to the many news clips, the documentary content on North Korea's YouTube channel did not explicitly advocate for North Korea's current political positions.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.24 no.2
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• pp.231-246
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• 2013

This paper attempts to explore the use of social metadata in academic libraries. A total of 173 academic libraries were examined and analyzed. Various social metadata were reviewed, involved with users' participation and contribution. Error-reports, tagging, recommendations, ratings, reviews, comments, sharing, and community were identified that support selection, sharing and collaboration through social engagement. Suggestions drawn from the findings are offered to utilize social metadata in order to enhance users' contribution and interaction. It is hoped that this exploratory study will provide insight into the use of social metadata in academic libraries.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.22 no.3
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• pp.189-206
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• 2011

This paper proposes a conceptual framework to explore the ways in which people work with in accessing, sharing, and navigating Web resources. In order to provide a better frame of a user's interaction with a folksonomy, an information foraging approach was adapted that denotes adaptive information seeking behaviors of users within human information interaction. A conceptual framework that consists of three different components from users' points of view was proposed: tagging, navigation, and knowledge sharing. This understanding will help us to motivate possible future directions of research in folksonomy and lay the groundwork for empirical research which focuses on qualitative analysis of a folksonomic and users' tagging behaviors.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.12
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• pp.1911-1916
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• 2013

One significant challenge that arises in social tagging systems is the rapid increase in the number and diversity of the tags. As opposed to structured annotation systems, tags provide users an unstructured, open-ended mechanism to annotate and organize web-content. In this paper, we propose a scheme for URL recommendation that is based on a folksonomy which is comprised of user-defined tags, URL-keywords and the category folder name as the major element. This scheme will be further improved and implemented on a browser extension that recommends to users the best way to classify a particular URL.

• Journal of the Korean Society for information Management
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• v.26 no.2
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• pp.127-147
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• 2009

The synonym issue is an inherent barrier in human-computer communication, and it is more challenging in a Web 2.0 application, especially in social tagging applications. In an effort to resolve the issue, the goal of this study is to test the feasibility of a Web 2.0 application as a potential source for synonyms. This study investigates a way of identifying similar tags from a popular collaborative tagging application, Delicious. Specifically, we propose an algorithm (FolkSim) for measuring the similarity of social tags from Delicious. We compared FolkSim to a cosine-based similarity method and observed that the top-ranked tags on the similar list generated by FolkSim tend to be among the best possible similar tags in given choices. Also, the lists appear to be relatively better than the ones created by CosSim. We also observed that tag folksonomy and similar list resemble each other to a certain degree so that it possibly serves as an alternative outcome, especially in case the FolkSim-based list is unavailable or infeasible.