• 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 Digital Convergence
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• v.18 no.9
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• pp.17-27
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• 2020

News articles and blog posts have influence on social agenda setting and this study applied text mining on the subject of solar PV in rural area appeared in those media. Texts are gained from online news articles and blog posts with rural solar PV as a keyword by web scrapping, and these are analysed by sentiment analysis and topic modeling technique. Sentiment analysis shows that the proportion of negative texts are significantly lower in blog posts compared to news articles. Result of topic modeling shows that topics related to government policy have the largest loading in positive articles whereas various topics are relatively evenly distributed in negative articles. For blog posts, topics related to rural area installation and environmental damage are have the largest loading in positive and negative texts, respectively. This research reveals issues related to rural solar PV by combining sentiment analysis and topic modeling that were separately applied in previous studies.

• International Journal of Knowledge Content Development & Technology
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• v.5 no.1
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• pp.15-32
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• 2015

This article analyzes motivations behind social sciences blog posts citing journal articles in order to find out whether blog citations are good indicators for the societal impact or benefits of research. A random sample of 300 social sciences blog posts (out of 1,233 blog posts) from ResearchBlogging.org published between 01/01/2012 to 18/06/2014 were subjected to content analysis. The 300 blog posts had 472 references including 424 journal articles from 269 different journals. Sixty-one (22.68%) of all cited journals were from the social sciences and most of the journals with high frequency were highly cited general science journals such as PNAS and Science. Seventy-five percent of all journals were referenced only once. The average age of articles cited at the time of citation was 5.8 years. Discussion and criticism were the two main categories of motivations. Overall, the study shows the potential of blog citations as an altmetric measure and as a proxy for assessing the research impact. A considerable number of citation motivations in blogs such as disputing a belief, suggesting policies, providing a solution to a problem, reacting to media, criticism and the like seemed to support gaining societal benefits. Societal benefits are considered as helping stimulate new approaches to social issues, or informing public debate and policymaking. Lower self-citation (compared to some other altmetric measures such as tweets) and the fact that blogging involves generating content (i.e. an intellectual process) give them an advantage for altmetrics. However, limitations and contextual issues such as disciplinary differences and low uptake of altmetrics, in general, in scholarly communication should not be ignored when using blogs as a data source for altmetrics.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.987-999
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• 2017

Extraction of influential people from their respective domains has attained the attention of scholastic community during current epoch. This study introduces an innovative interaction strength metric for retrieval of the most influential users in the online social network. The interactive strength is measured by three factors, namely re-tweet strength, commencing intensity and mentioning density. In this article, we design a novel algorithm called IPRank that considers the communications from perspectives of followers and followees in order to mine and rank the most influential people based on proposed interaction strength metric. We conducted extensive experiments to evaluate the strength and rank of each user in the micro-blog network. The comparative analysis validates that IPRank discovered high ranked people in terms of interaction strength. While the prior algorithm placed some low influenced people at high rank. The proposed model uncovers influential people due to inclusion of a novel interaction strength metric that improves results significantly in contrast with prior algorithm.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06a
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• pp.146-147
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• 2008

• 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.

• Information Systems Review
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• v.20 no.2
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• pp.163-188
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• 2018

When people try to find restaurant information via search engine results, they look at posts not only from sites with solely restaurant reviews but also from sites with restaurant unrelated contents. This study aims to investigate whether relevance between post and blog type affects users' trust toward a review. This study also attempts to check if the above effects interact with age. We designed a restaurant review post for two different blogs: one featuring restaurant review and another that does not feature restaurant reviews. After our participants visited one restaurant review post, they answered our questionnaire. We conducted an online survey on 206 participants to test our research model. Results show that 1) the effect of relevance between post and blog type on message credibility, which is users' trust toward restaurant reviews, is not greater when posts are consistent with the theme of a blog. 2) Among users who are over 30 years old, relevance between post and blog type moderates the relationship between media skepticism, which is users' feeling of mistrust toward blog, and belief in expertise, that is, users' belief that the review post provides sufficient restaurant information. 3) Users' perceived value of the restaurant review post mediates the relationship between users' belief in the expertise in a post and users' intention to seek additional information.

• 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.

• SUVANNABHUMI
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• v.15 no.2
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• pp.91-129
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• 2023

This paper reports the findings of a multimodal study conducted on 10 travel blog posts about Vietnam by seven British professional travel bloggers. The study takes a sociolinguistic view to tourism by seeing travel blogs as a source for linguistic and other semiotic materials while considering language as situated practice for the social construction of fundamental categories such as "human," "society," and "nation." It borrows concepts from Halliday's Systemic Functional Linguistics for interpersonal metafunction to develop an analytical framework to study how the co-occurrence of text and still images in these travel blog posts formulated the portrayal of Vietnam as a tourism destination and indicated the main sociolinguistic features of the blogs. The analysis of appreciation values and interactive qualities encoded in evaluative adjectives and still images show that Vietnam is generally portrayed as a country of identity and diversity. It provides tourists with positive experiences in terms of places of interest, food and local lifestyles and is cost-competitive. Strangerhood and authenticity are two outstanding sociolinguistic features exhibited in these travel blog posts. The findings of this study also underline the co-contribution of the linguistic sign, in this case evaluative adjectives, and the visual sign, in this case still images, as interpersonal meaning-making resources. To portray Vietnam, still images served as integral elements to evidence the credibility of verbal narrations. To unveil sociolinguistic characteristics of travel blogs, still images supported the linguistic realizations of authenticity and strangerhood on the posts, and in some case delivered an even stronger message than words. Not only does the study present a source of feedback from international travelers to tourism practice in Vietnam, but it also provides insights into multimodal analysis of tourism discourse which remains an under-researched area in Vietnam.

• Journal of the Korea Society of Computer and Information
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• v.16 no.1
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• pp.19-29
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• 2011

As people have heightened attention to blogs that are individual media, a variety rank algorithms was proposed for the blog search. These algorithms was modified for structural features of blogs that differ from typical web sites, and measured blogs' reputations or popularities based on the interaction results like links, comments or trackbacks and reflected in the search system. But actual blog search systems use not only blog-ranks but also search words, a time factor and so on. Nevertheless, those might not produce desirable results. In this paper, we suggest a topic-rank technique, which can find blogs that have significant degrees of association with topics. This technique is a method which ranks the relations between blogs and indexed words of blog posts as well as the topics representing blog posts. The blog rankings of correlations with search words are can be effectively computed in the blog retrieval by the proposed technique. After comparing precisions and coverage ratios of our blog retrieval system which applis our proposed topic-rank technique, we know that the performance of the blog retrieval system using topic-rank technique is more effective than others.