• Journal of Internet Computing and Services
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• v.17 no.3
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• pp.107-113
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• 2016

Following the recent advancement in the use of social networks, a vast amount of different online reviews is created. These variable online reviews which provide feedback data of contents' are being used as sources of valuable information to both contents' users and providers. With the increasing importance of online reviews, studies on opinion mining which analyzes online reviews to extract opinions or evaluations, attitudes and emotions of the writer have been on the increase. However, previous sentiment analysis techniques of opinion-mining focus only on the classification of reviews into positive or negative classes but does not include detailed information analysis of the user's satisfaction or sentiment grounds. Also, previous designs of the sentiment analysis technique only applied to one content domain that is, either product or movie, and could not be applied to other contents from a different domain. This paper suggests a sentiment analysis technique that can analyze detailed satisfaction of online reviews and extract detailed information of the satisfaction level. The proposed technique can analyze not only one domain of contents but also a variety of contents that are not from the same domain. In addition, we design a system based on Hadoop to process vast amounts of data quickly and efficiently. Through our proposed system, both users and contents' providers will be able to receive feedback information more clearly and in detail. Consequently, potential users who will use the content can make effective decisions and contents' providers can quickly apply the users' responses when developing marketing strategy as opposed to the old methods of using surveys. Moreover, the system is expected to be used practically in various fields that require user comments.

• International Commerce and Information Review
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• v.17 no.3
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• pp.3-27
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• 2015

As hostile online reviews can have a negative impact on a company's reputation, it is not surprising that online reviewers and business owners often get involved in conflicts which sometimes evolve into legal disputes. This research examines the legal dispute case in which the business owner charges an online reviewer for a defamation. Further, this research compares the supreme court's decision with general public's view on this defamation case, using a survey method. From the legal point of view, an online reviewer's primary motive determines whether the online reviews are defamatory statements or not. Specifically, if an online reviewer's primary motive is to increase the overall benefits for the public society, the online review does not bear any legal liability. According to our survey, consumers' view aligns with the final decision of the supreme court. They believe that online reviews should bear a minimum level of legal liability as online reviews often contain useful and valuable information which can enhance overall public benefits.

• The Journal of the Korea Contents Association
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• v.10 no.8
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• pp.38-50
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• 2010

In recent years, the number of users who are actively express their opinions about Internet articles is more and more growing up, as the use of cyber community such as weblog or Internet discussion board increases. In fact, it is not difficult to find an article with hundreds of comments in famous Internet discussion boards. Most of the weblogs or Internet discussion boards present comments in the form of list and do not yet support even the basic operation such as searching comments. In this paper, we analysed large sets of comments in Internet discussion board named AGORA. It was found that from the result that the distribution of comment writers follows power-law. So we suppose a new search structure of comments using skip lists. The main idea of our approach is to reflect the probabilistic distribution properties of the commenters following the power-law to the data structure. Our empirical results show that the proposed method performs more efficient in searching the nodes with fewer number of comparison operations than logN, which is the theoretical time complexity of general indexed structure such as B-trees or typical skip lists.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.263-271
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• 2016

Software requirement analysis is necessary for successful software development project. Specially, incomplete requirement is the most influential causes of software project failure. Incomplete requirement can bring late delay and over budget because of the misunderstanding and ambiguous criteria for project validation. Software requirement patterns can help writing more complete requirement. These can be a reference model and standards when author writing or validating software requirement. Furthermore, when a novice writes the software scenario, the requirement patterns can be one of the guideline. In this paper proposes an automatic approach to identifying software scenario patterns from various software scenarios. In this paper, we gathered 83 scenarios from eight industrial systems, and show how to extract 54 scenario patterns and how to find omitted action of the scenario using extracted patterns for the feasibility of the approach.

• The Journal of the Korea Contents Association
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• v.18 no.11
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• pp.135-145
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• 2018

In online communities, users use comments to exchange their opinions and feelings on various subjects. Communication based on comments is quick and convenient, but sometimes this light-weight characteristic makes users use impolite and aggressive words, which leads to an online conflict. Therefore, it is important to analyze and classify users according to their characteristics in order to predict and take action for this kind of troubles. In this paper, we present several quantitative measures for describing the structures of comments trees based on the assumption that the user characteristics be observed as a form of some structural feature in comment trees of articles in which they posted comments. We examine the distribution of the proposed measures over article posters and commenters, and in addition, we show the effectiveness of the presented structural features by conducting experiments to classify users who have received warnings of the administrator from benign users.

• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.575-582
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• 2020

We proposes a method to estimate political preference of users who write comments on internet news. We collected and analyzed a massive amount of new comment data from internet news to extract features that effectively characterizes political preference of users. We expect that it helps user to obtain unbiased information from internet news and online discussion by providing estimated political stance of news comment writer. Through comprehensive tests we prove the effectiveness of two proposed methods, lexicon-based algorithm and similarity-based algorithm.

• Korean journal of communication and information
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• v.75
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• pp.43-79
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• 2016

An increase in the number of immigrants to Korea since the late 1980s' has signified the proliferation of globalization and global capitalism. In Korea, most married immigrants are women, as the culture emphasizes patrilineage and the stability of the institution of marriage, particularly in rural areas. Immigrant women have experienced dual ordeals. The Aogra Internet community in Korea has been one of the most representative sites that has shown the power of communities in cyberspace since 2002, leading the discussion of social issues and deliberative democracy both online and offline. This paper analyzed Koreans' writings (such as long comments) on immigrant women in the Agora community. The analysis revealed the following results: first, immigrant women were referred to using terms related to prostitution, with excessive expression of disgust, which is called a "narrative of identity." Second, anti-multiculturalists called Korean men victims of married immigrant women and expressed hatred toward immigrant women, which is called a "narrative of sacrifice." Third, anti-multiculturalists justified their emotions as just resentment based on ideas of justice, equality, and patriotism, concealing the emotion of disgust, which is called the "narrative of justice, equality." Fourth, antimulticulturalists played roles to spread the emotion of disgust, by repeatedly referring to international marriage fraud and immigrant workers' crimes, which is called "narrative of crime." Fifth, some positive writings on immigrant women were based on empathy(a concept defined in this context by Martha Nussbaum), but they can be analyzed as narratives encouraging cultural integration through the perspective of orientalism. Therefore, comments on immigrant women in the Agora represent a "catch-22" dilemma. To deal with conflicts arising from disgust and violations of human rights, civic education focusing on humanism is needed in this multicultural era.

• Information Systems Review
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• v.22 no.4
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• pp.163-184
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• 2020

The information on SNS, which is created by the forms of postings and comments, is being magnified and redistributed to news media expanding its impacts on real words. This amplifying effects of SNS comments have been increasingly discussed but there still lacks the answers for which dimensions of information is magnified, and what affects the direction and the degree of the amplification. This study, therefore, explores the detailed dimensions that are magnified by SNS comments and how SNS posting structure and social network characteristics affect them by using sentiment analysis. By analyzing 2,378 Facebook postings and news articles and their 26,312 SNS and 74,730 news site comments, this study shows that SNS comments magnify the sentiments of the posting articles they are attached to. In comparison to news site comments, SNS comments magnify the cognitive and social dimensions more than the news site comments. In the affective dimension, they tend to magnify only the positive emotion more than news site comments. Also, the findings reveal that whether the article in the posting is written by the posting owner affects the degree of amplification when the comments are remained positive or switched positive, while the opposite determines the amplification when comments remain negatively, suggesting that the user relationship in social network is the important factor that affects the direction and the degree of the information amplification in SNS.

• Proceedings of the Korean Society of Computer Information Conference
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• 2015.01a
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• pp.11-14
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• 2015

많은 블로그 제공 사이트는 블로그 포스트 작성자에게 미리 정의된 범주 (category)에 따라 포스트의 주제에 대하여 범주를 선택할 수 있는 환경을 제공한다. 그러나 블로거들은 작성한 포스트의 범주를 매번 수동으로 선택해야 하는 불편함이 있다. 이러한 불편함의 해결을 위해 블로그 포스트를 자동으로 분류해주는 기능을 제공한다면 블로그의 활용성이 증가할 것이다. 기존의 블로그 문서 분류의 연구는 각 범주의 고유 정보를 반영하는 것에 한계가 있었다. 이러한 문제를 해결하기 위해, 본 논문에서는 범주별 고유 정보를 반영한 어휘 가중치를 제안한다. 어휘 가중치의 분석을 위하여 범주별로 블로그 문서를 수집하고, 수집한 문서에서 어휘의 빈도와 문서의 빈도, 범주별 어휘빈도 등을 고려하여 새로운 지표인 CTF, CDF, IECDF를 개발하였다. 이러한 지표를 기반으로 기존의 Naive Bayes 알고리즘으로 학습하여, 블로그 포스트를 자동으로 분류하였다. 실험에서는 본 논문에서 제안한 가중치 방법인 TF-CTF-CDF-IECDF를 사용한 분류가 가장 높은 성능을 보였다.

• Annual Conference of KIPS
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• 2017.11a
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• pp.849-852
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• 2017

본 논문에서는 SNS에서 수집한 데이터를 이용하여 사회 불안의 시공간 분포를 시각화 하는 기법을 소개한다. Open API인 twitter4j를 이용하여 트위터로부터 시공간 정보를 포함한 데이터를 수집한 뒤, 이 트윗의 작성자가 불안한지 아닌지 표시한 훈련 데이터를 준비한다. 이 훈련 데이터와 한글 형태소 분석기 Open API인 KOMORAN을 이용해 사전을 구축하고, 불안 분류기를 개발한다. 트위터로부터 수집한 시공간 정보를 포함한 데이터를 분류기로 분류하여, 지도에 표시해줌으로써 사회 불안을 시각화 한다. 사회 과학자들이 이를 이용하여 불안을 체계적으로 연구함으로써 불안으로부터 생기는 다양한 사회 문제들을 해결할 수 있다.