• Proceedings of the Korean Society of Computer Information Conference
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• 2017.07a
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• pp.344-345
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• 2017

Opinion mining and sentiment analysis(OMSA) as a research discipline has emerged during last 15 years and provides a methodology to computationally process the unstructured data mainly to extract opinions and identify their sentiments. The relatively new but fast growing research discipline has changed a lot during these years. This paper presents a scientometric analysis of research work done on OMSA during 2007-2016. For the literature analysis, research publications indexed in Web of Science (WoS) database are used as input data. The publication data is analyzed computationally to identify year-wise publication pattern, rate of growth of publications, research areas.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.1
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• pp.133-140
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• 2011

For both customers and companies, it is very important to analyze online customer reviews, which consist of small documents that include opinions or experiences about products or services, because the customers can get good informations and the companies can establish good marketing strategies. In this paper, we propose the association model for the opinion mining which can analyze customer opinions posted on web. The association model is to modify the association rules mining model in data mining in order to apply efficiently and effectively the association mining techniques to the opinion mining. We designed and implemented the opinion mining systems based on the modified association model and the grouping idea which would enable it to generate significant rules more.

• Journal of the Korean Society for information Management
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• v.25 no.4
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• pp.115-129
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• 2008

Recently, as its growth and popularization, the Web is changed into the place where people express, share and debate their opinions rather than the space of information seeking. Accordingly, the needs for searching opinions expressed in the Web are also increasing. However, it is difficult to meet these needs by using a classical information retrieval system that only concerns the relevance between the user's query and documents. Instead, a more advanced system that captures subjective information through documents is required. The proposed system effectively retrieves opinionated documents by utilizing an existing information retrieval system. This paper proposes a kind of hybrid method which can utilize both a dictionary-based opinion analysis technique and a machine learning based opinion analysis technique. Experimental results show that the proposed method is effective in improving the performance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.05a
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• pp.537-541
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• 2001

This study is to construct ODBC Database based Web, which has a structure of Web server and Database server connected with Database concerning server demand for the purpose of the efficient record, use and management of various document data. Each ASP OLE DB ran be saved and inferred by measuring CLC and ULC. That makes to record, use and management of document data more convenient. For the application of the suggested of the system this study is to put together into 6 categories and generalize the synthetic opinion column of high school student document.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.6 no.4
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• pp.195-200
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• 2013

This paper proposes an SNS and Web Data Analytics System which can utilize a business marketing strategy by analyzing negative SNS and Web Data that can do great damage to a business image. It consists of the Data Collection Module collecting SNS and Web Data, the Hbase Module storing the collected data, the Data Analysis Module estimating and classifying the meaning of data after an semantic analysis of the collected data, and the PHS Module accomplishing an optimized Map Reduce by using SNS and Web data involved a Businesse. This paper can utilize this analysis result for a business marketing strategy by efficiently managing SNS and Web data with these modules.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.160-161
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• 2017

Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language Opinion mining and sentiment analysis(OMSA) as a research discipline has emerged during last 15 years and provides a methodology to computationally process the unstructured data mainly to extract opinions and identify their sentiments. The relatively new but fast growing research discipline has changed a lot during these years. This paper presents a scientometric analysis of research work done on OMSA during 2007-2016. For the literature analysis, research publications indexed in Web of Science (WoS) database are used as input data. The publication data is analyzed computationally to identify year-wise publication pattern, rate of growth of publications, research areas. More detailed manual analysis of the data is also performed to identify popular approaches (machine learning and lexcon-based) used in these publications, levels (documents, sentences or aspect-level) of sentiment analysis work done and major application areass of OMSA.

• Asian Journal for Public Opinion Research
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• v.1 no.4
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• pp.268-291
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• 2014

Social media is becoming more and more important in social movements. This study, adopting the web mining approach, attempts to investigate how social media, Facebook in particular, functioned in the "May 25 Protest" and the "May 27 Protest", two movements which broke out in Macao on 25 and 27 May 2014, respectively, against the Retirement Package Bill. In the two protests, Macao residents deployed Facebook to share information and motivated people's participation. Twelve events (181,106 people invited) and 36 groups/pages (41,266 members) related on Facebook were examined. Results showed that the information flow on Facebook fluctuated in accordance with the event development in reality. Multiple patterns of manifestation, such as video of adopted news or songs, designed profile (protest icon), original ironic pictures, self-organized clubs by undergraduates and white T-shirts as a symbol, among others, appeared online and interacted with offline actions. It was also found that social media assisted the information diffusion and provided persuasive reasons for netizens to join the movement. Social media helped to expand movement influence in providing a platform for diversified performances for actions taken in a protest, which could express and develop core and consistent movement repertoire.

• KIISE Transactions on Computing Practices
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• v.22 no.7
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• pp.338-343
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• 2016

Today, opinion reviews on the Web are often used as a means of information exchange. As the importance of opinion reviews continues to grow, the number of issues for opinion spam also increases. Even though many research studies on detecting spam reviews have been conducted, some limitations of gold-standard datasets hinder research. Therefore, we introduce a new dataset called "Paraphrased Opinion Spam (POS)" that contains a new type of review spam that imitates truthful reviews. We have noticed that spammers refer to existing truthful reviews to fabricate spam reviews. To create such a seemingly truthful review spam dataset, we asked task participants to paraphrase truthful reviews to create a new deceptive review. The experiment results show that classifying our POS dataset is more difficult than classifying the existing spam datasets since the reviews in our dataset more linguistically look like truthful reviews. Also, training volume has been found to be an important factor for classification model performance.

• Interdisciplinary Bio Central
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• v.3 no.3
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• pp.12.1-12.3
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• 2011

Bioinformatics tools and databases are useful for understanding and processing various biological data. Numerous resources are being published each year. It is not a trivial task to find up-to-date relevant tools and databases. Moreover, no server is available to provide comprehensive coverage on bioinformatics resources in all biological fields. Here, we present a directory server called IntoPub that provides information on web resources. First, we downloaded XML-formatted abstracts containing web URLs from the NCBI PubMed database by using 'ESearch-EFetch' function in the NCBI E-utilities. The information is obtained from abstracts in the PubMed by extracting 'www' or 'http' prefixes. Then, we cu-rate the downloaded abstracts both in automatic and manual fashion. As of July 2011, the IntoPub database has 12,118 abstracts containing web URLs from 174 journals. Our anal-ysis shows that the number of abstracts containing web resources has increased signifi-cantly every year. The server has been tested by many biologists from several countries to get opinion on user satisfaction, usefulness, practicability, and ease of use since January 2010. In the IntoPub web server, users can easily find relevant bioinformatics resources, as compared to searching in PubMed. IntoPub will continue to update and incorporate new web resources from PubMed and other literature databases. IntoPub, available at http://into.kobic.re.kr/, is updated every day.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.2
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• pp.222-226
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• 2010

With the continuously increasing volume of e-commerce transactions, it is now popular to buy some products and to evaluate them on the World Wide Web. The product reviews are very useful to customers because they can make better decisions based on the indirect experiences obtainable through these reviews. However, since online shopping malls do not provide ranking results, it is not easy for users to read all the relevant review documents effectively. Product reviews include subjective and emotional opinions. Thus, the review search is different from the general web search in terms of ranking strategy. In this paper, we propose an effective method of ranking the reviews that can reflect user's intention by using opinion mining techniques. The proposed method analyzes product reviews with query words, and sentimental polarity of subjective opinions. Through diverse experiments, we show that our proposed method outperforms conventional ones.