• Journal of the Korean Society of Clothing and Textiles
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• v.35 no.9
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• pp.1028-1038
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• 2011

A blog has significant effect as a new online medium and as a tool to share information with its powerful networking function. Blogs are established based on personal experience and their impact is stronger than conventional media in terms of informativeness, credibility and interactivity. Such characteristics of blogs lead to blog commitment (a phenomenon that has behavioral consequences) that eventually influences consumer fashion purchase behavior. The more a consumer is interested in fashion and seeks diverse information from a wide range of media, the more personally committed they become to certain blogs; in addition, they will also post the results of their fashion product purchases on their blog to further create and reproduce information. This research discovers how blog commitment affects fashion product purchase behavior and information reproduction activity among consumers as well as explores the impact of blog characteristics and information variety seeking by individual consumers on these factors. The data was collected from 428 adults who purchased a fashion product based on information they found on a blog. The results are as follows. First, blog characteristics are composed of accessibility, interactivity, credibility of the information, and informativeness. Second, in terms of the blog commitment, informativeness, credibility, and consumer information diversification (respectively), turned out to have positive effects; in addition, accessibility and credibility had positive effects for corporate blogs. The comparison between private and corporate blogs showed that consumers tend to be more committed to private blogs. Third, in terms of the brand attitude, private/corporate blog commitment, credibility, and consumer information diversification (respectively) had a positive influence. Fourth, blog characteristics and consumer information diversification led consumers (through private/corporate blog commitment) to form a favorable attitude towards the brand and purchase products that resulted in information reproduction of the purchased product.

• Proceedings of the Korean Information Science Society Conference
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• 2010.11a
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• pp.48-49
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• 2010

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.1
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• pp.58-62
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• 2015

Most blog sites provide predefined classes based on contents or topics, but few bloggers choose classes for their posts because of its cumbersome manual process. This paper proposes an automatic blog post classification method that variously combines term frequency, document frequency and class frequency from each classes to find appropriate weighting scheme. In experiment, combination of term frequency, category term frequency and inversed (excepted category's) document frequency shows 77.02% classification precisions.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.11
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• pp.1121-1125
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• 2010

This paper proposes a Wikipedia-based feedback method for in-depth blog distillation whose goal is to find blogs that represent in-depth thoughts or analysis on a given query. The proposed method uses Wikipedia articles which are relevant to the query. TREC Blogs08 collection which is a large-scale blog corpus and English Wikipedia dump were used for experiments, The proposed method significantly increased the retrieval performance including MAP over the conventional post based feedback method.

• Journal of KIISE:Software and Applications
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• v.37 no.2
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• pp.137-147
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• 2010

A blog is a website, usually maintained by an individual, with regular entries of commentary, descriptions of events, or other material such as graphics or video. Entries are commonly displayed in reverse chronological order. Blog search engines, like web search engines, seek information for searchers on blogs. Blog search engines sometimes output unsatisfactory results, mainly due to spam blogs or splogs. Splogs are blogs hosting spam posts, plagiarized or auto-generated contents for the sole purpose of hosting advertizements or raising the search rankings of target sites. This thesis focuses on splog detection. This thesis proposes a new splog detection method, which is based on blog post structure similarity and posting count per day. Experiments based on methods proposed a day show excellent result on splog detection tasks with over 90% accuracy.

• The Journal of Society for e-Business Studies
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• v.16 no.4
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• pp.301-319
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• 2011

Blog plays an important role as new type of knowledge base distinguishing from traditional web resource. While information resources in their existing website dealt with a wide range of topics, information resources of the blog are concentrated in specific units of information depending on the user's interests and have the criteria of classification forresources published by tagging. In this research, we build a tag hierarchy utilizing title keywords and tags of the blog, and propose apost clustering methodology applying the tag hierarchy. We then generate the tag hierarchy reflected the relationship between tags and develop the tag clustering methodology according to tag similarity. In this paper, we analyze the possibility of applying the proposed methodology with real-world examples and evaluate its performances through developed prototype system.

• Journal of KIISE:Databases
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• v.36 no.6
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• pp.411-421
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• 2009

In a blog network, there are special users who induce other users to actively utilize blog services. In this paper, these users whose contents exhibit large influence over other bloggers are defined as 'Content Power Users' (CPUs). It is important to accurately determine who content power users are in a blog network in order to establish business policies that will stimulate usage of blog services. In this paper, we discuss a novel method of determining content power users. First, we propose a system of measuring the influence of content of each post owned by individual users. Then, by adjusting the measured values based on the time of exposure and adding them up, we calculate the power of influence for corresponding users. Finally, by applying the proposed method to actual blog networks and comparing the selected power users to those of a preexisting method, we analyze different methods of determining power users. The experimental results demonstrate that our method of determining power users reflects well dynamic changes in a blog network.

• Journal of Digital Contents Society
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• v.18 no.3
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• pp.551-558
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• 2017

The growth of blogs has two aspect of providing various information and marketing. This study collected the rankings of blog posts of large portal using OpenAPI and investigated the features of blogs ranked through the exploratory data analysis technique. As a result of the analysis, it was found that the influence of the blogger and the recent creation date of the post were highly influential factors in the top rank. Due to the weakness of these evaluation algorithms, there was a problem of showing the search results which is concentrated to the power blogger's post. In this study, we propose an algorithm that improves the reliability of content by adding the reliability DB information which is verified by the experts and reflects the fairness of the application of the ranking score through the trend index indicating various public interests. Improved algorithms have made it possible to provide more reliable information in the search results of the relevant field and have an effect of making it difficult to manipulate ranking by illegal applications that increase the number of visitors.

• Journal of KIISE
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• v.42 no.5
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• pp.637-641
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• 2015

Due to the recent increasement of user created contents like SNS, blog posts, and so on, broadcast contents are actively re-construction by its users. Especially, on some genres like drama, movie, various information from cars and film sites to clothes and watches in a content is spreaded out to other users through blog postings. Since such information can be an additional information for the content, they can be used for providing high-quality broadcast services. For this purpose, in this paper, we propose timeline tag cloud generation method for broadcasting contents. In the proposed method, blog postings on the target contents are first gathered and then, images and words around images are extracted from a blog post as a tag set. An extracted tag set is tagged on a specific timeline of the target content. In experiments, to prove the efficiency of the proposed method, we evaluated the performances of the proposed image matching and tag cloud generation methods.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.6
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• pp.1-8
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• 2019

Recently, consumer distrust has deepened due to blog posts focusing only on public relations due to 'viral marketing'. In addition, marketing projects such as false writing or exaggerated use of the latter phase are one of the most popular programs in 2016 as they are cheaper and more effective than newspaper and TV ads, and the size of advertising costs is set to be a major means of advertising at '3 trillion 394.1 billion won. From this 'viral marketing,' it has become an Internet environment that needs tools to filter information. The fake review filtering application ADDAVICHI presented in this paper extracts, analyzes, and presents blog keywords, total number of searches, reliability and satisfaction when users search for content such as "event" and "taste restaurant." Reliability shows the number of ad posts on a blog, the total number of posts, and satisfaction shows a clean post with confidence divided into positive and negative posts. Finally, the keyword shows a list of the top three words in the review from a positive post. In this way, it helps users interpret information away from advertising.