• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.929-930
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• 2009

본 논문에서는 링크 기반 유사도 계산을 이용해서 블로그 공간에서 사용자가 관심을 가질만한 게시글들을 사용자에게 추천하는 방안을 제안한다. 제안된 방안은 사용자가 관심을 가졌던 게시글들 중에서 시드 게시글을 선택하고 링크 기반 유사도를 계산하여 시드 게시글과 가장 유사하다고 판단되는 k개의 게시글들을 사용자에게 추천한다. 또한, 시드 게시글들 중에서 추천하고자 하는 주제가 아닌 다른 주제의 게시글들이 잘못 추천되는 문제를 해결하기 위해서 시드 게시글과 동일한 주제라고 확실시 되는 게시글들만을 점진적으로 찾아 추천하는 방안을 제안한다. 실제 블로그 데이터를 이용한 실험을 통하여 제안하는 추천 방안의 우수성을 검증한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.372-374
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• 2009

본 논문에서는 블로그 공간에 존재하는 블로거와 포스트들을 링크 기반 클러스터링을 통해 클러스터링하고자 한다. 먼저 기존 링크 기반 클러스터링 방안 중에서 블로거와 포스트들을 클러스터링하는데 가장 적합한 LinkClus를 선택한다. LinkClus를 블로그 공간에 적용하기 위해서 블로거와 포스트를 각각 하나의 타입으로, 블로거와 포스트 사이의 액션을 링크로 사상한다. 정확한 클러스터링을 위하여 클러스터의 대상을 여러 주제에 관심을 가지는 블로거 대신 하나의 주제만을 나타내는 폴더로 한다. 또한 노이즈의 발생 가능성을 높이는 링크가 아주 적은 블로거와 포스트를 클러스터링 과정에서 제외 시킨다. 실험을 통하여 제안하는 방안을 이용한 클러스터링 결과가 내용적으로도 유사한지 검증한다.

• Journal of the Korean Geographical Society
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• v.51 no.1
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• pp.109-125
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• 2016

Human life has been inextricably linked with healing. Recently, as the demands of healing are higher, it is more necessary to study spaces, places and mobilities related to healing in geographical studies. This paper draws on a case study of urban peoples walks along Seoul City Wall to explore what healing factors affect the people walking along historical landscapes in urban center and understand geographical implications of the healing process. Based on the concept and analytical lens of 'therapeutic mobilities' introduced by Gatrell, this research analyzes texts written on 181 blogs. The results show the main factors that affect their healing are 'weather climate', 'walk stroll', and 'nightscape'. Futhermore, the blogs' narratives focusing on these main factors imply healing place-making, time as limiting factor, and the social body within nightscape in the healing process.

• Journal of Information Science Theory and Practice
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• v.1 no.2
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• pp.36-57
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• 2013

Blogs are readily available sources of opinions and sentiments which allows bloggers to exert a certain level of influence over the blog readers. Previous studies had attempted to analyze blog features to detect influence within the blogosphere, but had not studied in details influence at the blogger-level. Other studies studied bloggers' personalities with regards to their propensity to blog, but did not relate the personalities of bloggers to influence. Bloggers may differ in their way or manner of exerting influence. For example, bloggers could be active participants or just passive shares, or whether they express ideas in a rational or subjective manner, or they are received positively or negatively by the readers. In this paper, we further analyze the engagement style (frequency, scope, originality, and consistency of the blog postings), persuasion style (appeals to reasons or emotions), and persona (degree of compliance) of individual bloggers. Methods used include similarity analysis to detect the sharing-creating aspect of engagement style, subjectivity analysis to measure persuasion style, and sentiment analysis to identify persona style. While previous studies analyzed influence at blog site level, our model is shown to provide a fine-grained influence analysis that could further differentiate the bloggers' influence style in a blog site.

• Journal of KIISE:Databases
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• v.37 no.1
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• pp.56-69
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• 2010

In blogspace, there are posts that deal with a common topic and bloggers that are interested in these posts. In this paper, we define a blog community as a group of these bloggers and posts. With a blog community, we can establish various business policies for target marketing, sharing high quality data, and mobilizing the activities in the blogspace. Unlike internet cafes, bloggers participate in blog communities without explicit membership. So, it is not easy to identify the members of a community. In this paper, we propose an effective approach for extracting a blog community that is related to a given topic. First, we choose seed posts that is highly related to a given topic, and select bloggers that are related to the topic with the seed posts. Then, we select posts that are related to the topic with the selected bloggers. By repeating this, we find all the posts and bloggers that are members of the community related to a given topic in blogspace. We verify the superiority of the proposed approach by analyzing extracted blog communities.

• Journal of Korean Library and Information Science Society
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• v.46 no.1
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• pp.321-344
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• 2015

This paper presents a fusion approach to sentiment detection that combines multiple sources of evidence to retrieve blogs that contain opinions on a specific topic. Our approach to finding opinionated blogs on topic consists of first applying traditional information retrieval methods to retrieve blogs on a given topic and then boosting the ranks of opinionated blogs based on the opinion scores computed by multiple sentiment detection methods. Our sentiment detection strategy, whose central idea is to rely on a variety of complementary evidences rather than trying to optimize the utilization of a single source of evidence, includes High Frequency module, which identifies opinions based on the frequency of opinion terms (i.e., terms that occur frequently in opinionated documents), Low Frequency module, which makes use of uncommon/rare terms (e.g., "sooo good") that express strong sentiments, IU Module, which leverages n-grams with IU (I and you) anchor terms (e.g., I believe, You will love), Wilson's lexicon module, which uses a collection-independent opinion lexicon constructed from Wilson's subjectivity terms, and Opinion Acronym module, which utilizes a small set of opinion acronyms (e.g., imho). The results of our study show that combining multiple sources of opinion evidence is an effective method for improving opinion detection performance.

• Korean Management Science Review
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• v.26 no.3
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• pp.185-204
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• 2009

Power bloggers have become one of the most important resources of blog service companies, and only those who attract and secure power bloggers will be able to have competitive edge and profitability in blog related businesses. This study examines the effects of technology acceptance factors and economical factors on the loyalty of power bloggers. The analysis results show that the usefulness, power of social influence and enjoyment positively affect the attitude and intention to continuous use. The relationship between the attitude and intention to continuous use is demonstrated as significant. The economical benefit exhibits weakly positive influence on the attitude to blogging, but not on the intention. This indicates that although many power bloggers receive economic benefits through their blogging activities, such economical benefits do not have big impact on their activities and the intention to use. The blog service providers may use the analysis results when developing new blog services. In particular, the usefulness, which is often considered as one of the most important factors in the success of the blogosphere, is found to have less impact than the enjoyment among power bioggers. This is because blog users, especially power bloggers, use the blog not for a specific purpose or for generating a special product; most of them use the blog to satisfy their own personal desires. When developing blog services, therefore, it is important to cater to the users' enjoyment and their psychological compensation. What is surprising is that the effect of the economical factor is not ad significant as one might have expected. This implies that the new blog services that provide profit sharing or advertising revenue sharing may not be as successful as one would have hoped for in maintaining the loyalty of power bloggers.

• Journal of KIISE:Software and Applications
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• v.35 no.4
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• pp.219-233
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• 2008

This paper suggests an intelligent semantic blog model to systematically analyze and manage biogosphere with ontology as its conceptual knowledge base. In the model, the system managers may support users to easily find appropriate blog resources by tracking and analyzing various relationships between ontology - they may intelligently recommend Interest blog communities to relevant users by monitoring interaction activities in blogoshpere, dynamically grouping the communities with the ontology. To systematically specify the functionality of our model, 1) we first express the structure of blog resources in terms of objects and relationships between them and then 2) we formalize a set of operators designed to be applied to the resources. System queries are implemented by the combination of the operators.

• The Journal of Society for e-Business Studies
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• v.17 no.4
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• pp.69-93
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• 2012

Various influence-related relationships in Social Network Services (SNS) among users, posts, and user-and-post, can be expressed using links. The current research evaluates the influence of specific users or posts by analyzing the link structure of relevant social network graphs to identify influential users. We applied the concept of mutual interactions proposed for ranking semantic web resources, rather than the voting notion of Page Rank or HITS, to blogosphere, one of the early SNS. Through many experiments with network models, where the performance and validity of each alternative approach can be analyzed, we showed the applicability and strengths of our approach. The weight tuning processes for the links of these network models enabled us to control the experiment errors form the link weight differences and compare the implementation easiness of alternatives. An additional example of how to enter the content scores of commercial or spam posts into the graph-based method is suggested on a small network model as well. This research, as a starting point of the study on identifying influential users in SNS, is distinctive from the previous researches in the following points. First, various influence-related properties that are deemed important but are disregarded, such as scraping, commenting, subscribing to RSS feeds, and trusting friends, can be considered simultaneously. Second, the framework reflects the general phenomenon where objects interacting with more influential objects increase their influence. Third, regarding the extent to which a bloggers causes other bloggers to act after him or her as the most important factor of influence, we treated sequential referencing relationships with a viewpoint from that of PageRank or HITS (Hypertext Induced Topic Selection).