• Journal of Environmental Impact Assessment
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• v.20 no.3
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• pp.397-409
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• 2011

This study was carried out for improving the effectiveness of water resources development project through local resident opinions in the environmental impact assessment(EIA). The EIA reports of seven dams were examined. Four dams -Youngju Dam, Seongduck Dam, Buhang Dam and Hantangang Dam- which included many local opinions including 470 opinions of 341 local residents were selected to be analyzed. Local residents submitted their opinions in the six fields which are meteorological phenomena, water quality, land use, fauna and flora, noise and vibration, and residence, and the major opinions of those opinions came from the atmosphere environment field which is 32% of total opinions and social and economic field which is 38% of total opinions, respectively. In submerged area, opinions of the measure for migration and compensation were 91% and in non-submerged area, opinions of the measure for meteorological phenomena was 86%. Those percentages were maximum in each area. Opinions concerned meteorological phenomena were 86% and 53% in Youngju Dam and Seongduck Dam where area is surrounded by existing dam, but there was only 9% and 0% of opinions in Buhang Dam and Hantangang Dam where area is without existing dam nearby. The reformation methods which reflected the resident's opinions were suggested on EIA in dam development projects. First of all, reliability and objectivity of the field of meteorological phenoma should be enhanced by scientific prediction of the phenomenon days. Secondly, techniques reducing uncertainty of various water quality prediction models ought to be developed and effectiveness of the reduction strategies in environmental impact should be quantified. Finally, the draft of EIA report should involve the detailed plans of migration and compensation's procedures, criteria and measures to support.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1825-1844
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• 2019

Political campaigns circulate manipulative opinions in online communities to implant false beliefs and eventually win elections. Not only is this type of manipulation unfair, it also has long-lasting negative impacts on people's lives. Existing tools detect political manipulation based on a supervised classifier, which is accurate when trained with large labeled data. However, preparing this data becomes an excessive burden and must be repeated often to reflect changing manipulation tactics. We propose a practical detection system that requires moderate groundwork to achieve a sufficient level of accuracy. The proposed system groups opinions with similar properties into clusters, and then labels a few opinions from each cluster to build a classifier. It also models each opinion with features deduced from raw data with no additional processing. To validate the system, we collected over a million opinions during three nation-wide campaigns in South Korea. The system reduced groundwork from 200K to nearly 200 labeling tasks, and correctly identified over 90% of manipulative opinions. The system also effectively identified transitions in manipulative tactics over time. We suggest that online communities perform periodic audits using the proposed system to highlight manipulative opinions and emerging tactics.

• Korean Institute of Interior Design Journal
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• v.19 no.5
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• pp.113-121
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• 2010

This study aimed to examine academic researches about apartment unit plans and consumer's opinions, and then to analyze the corelationship between the two, thus identifying the differences between the reality of housing market and consumers' opinionsl. On the analysis of the apartment unit plans($66m^2{\sim}164m^2$) provided by top 8 construction companies from March 2004 to December 2008. The remarkable change compared to existing apartments is an increase in the number of bays. This displays construction companies are responding to consumer' opinions actively. However, there were spaces which did not or passively reflect consumer's opinions enough. Especially, front side allocation of bedrooms beside master bedroom, kitchen/dining room and L-D-K & LD-K installation of a door between entrance and a living room. These are opinions that companies need to make efforts to reflect on apartment unit plans as much as possible.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.9 no.2
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• pp.33-44
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• 2006

The purpose of this study is to establish future directions of environmentally-friendly restoration of Yangjae underground stream and reflect various opinions of inhabitant in the plan and design process. The opinions from the citizens include the economic and environmental suitability of the restoration projects and preference for the future directions of restoration. The citizens are favorable to removing the existing parking lot and want to have jogging course, walking path and bike road in the stream. Different opinions and resulted in preferred facilities and diminishing existing park along the stream depending on the restoration influencing zone. As a result, citizens agree in restoration but they have different opinions about the feasibility of new facilities, streams restoration and central park reduction locally. It is desirable to reflect the opinions of citizens in the process of plan and design of restoration project.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.206-211
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• 2021

Internet users are increasingly invited to express their opinions on various subjects in social networks, e-commerce sites, news sites, forums, etc. Much of this information, which describes feelings, becomes the subject of study in several areas of research such as: "Sensing opinions and analyzing feelings". It is the process of identifying the polarity of the feelings held in the opinions found in the interactions of Internet users on the web and classifying them as positive, negative, or neutral. In this article, we suggest the implementation of a sentiment analysis tool that has the role of detecting the polarity of opinions from people about COVID-19 extracted from social media (tweeter) in the Arabic language and to know the impact of the pre-processing phase on the opinions classification. The results show gaps in this area of research, first of all, the lack of resources when collecting data. Second, Arabic language is more complexes in pre-processing step, especially the dialects in the pre-treatment phase. But ultimately the results obtained are promising.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.52-58
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• 2021

Questionnaires and surveys are increasingly being used to collect information from participants of empirical software engineering studies. Usually, such data is analyzed using statistical methods to show an overall picture of participants' agreement or disagreement. In general, the whole survey population is considered as one group with some methods to extract varieties. Sometimes, there are different opinions in the same group, but they are not well discovered. In some cases of the analysis, the population may be divided into subgroups according to some data. The opinions of different segments of the population may be the same. Even though the existing approach can capture the general trends, there is a risk that the opinions of different sub-groups are lost. The problem becomes more complex in longitudinal studies where minority opinions might fade over time. Longitudinal survey data may include several interesting patterns that can be extracted using a clustering process. It can discover new information and give attention to different opinions. We suggest using a data mining approach to finding the diversity among the different groups in longitudinal studies. Our study shows that diversity can be revealed and tracked over time using the clustering approach, and the minorities have an opportunity to be heard.

• The Journal of Information Systems
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• v.20 no.2
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• pp.21-36
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• 2011

The Web has become an excellent source for gathering consumer opinions. There are now numerous Web sites containing such opinions, e.g., customer reviews of products, forums, discussion groups, and blogs. This paper focuses on online customer reviews of products. It makes some contributions. Especially it proposes minimalism and chunking framework for analyzing and comparing consumer opinions of competing products. Users are able to clearly see the strengths and weaknesses of each product in the minds of consumers in terms of various product features. This comparison is useful to both potential customers and product manufacturers. For a product manufacturer, the comparison enables it to easily gather marketing intelligence and product benchmarking information. In this paper, we only focus on mining opinion/product features that the reviewers have commented on. Five types of online review presentations are presented to mine such features. Our experimental results show that these techniques are useful to identify customers' opinions and trends.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.659-662
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• 1998

In this paper, lower and upper possibility distributions are identified to reflect two extreme opinions in portfolio selection problems based on upper and lower possibility distributions are formalized as quadratic programming problems. Portfolios for compromising two extreme opinions from upper and lower possibility distributions and balancing the opinions of a group of experts can be obtained by quadratic optimization problems, respectively.

• The Journal of Information Technology
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• v.12 no.3
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• pp.7-17
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• 2009

This research is about the design of an opinion drawing and analysis system through statistical based Web Mining of web contents, where data of opinions are automatically drawn and analyzed concerning web documents that are scattered around in various web sites that exist within the internet. Furthermore, provides a search service that can easily classify positive/negative opinions and also provide searching and statistical information. Users, who want to search for opinions, can input a specific keyword to observe opinions of others easily. In addition, there is a merit in materializing the monitoring system.

• Journal of Information Processing Systems
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• v.9 no.4
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• pp.538-547
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• 2013

In this paper, we propose a bias detection method that is based on personal and social opinions that express contrasting views on competing topics on Twitter. We used unsupervised polarity classification is conducted for learning social opinions on targets. The $tf{\cdot}idf$ algorithm is applied to extract targets to reflect sentiments and features of tweets. Our method addresses there being a lack of a sentiment lexicon when learning social opinions. To evaluate the effectiveness of our method, experiments were conducted on four issues using Twitter test collection. The proposed method achieved significant improvements over the baselines.