• Journal of the Korean Society for Aviation and Aeronautics
• /
• v.18 no.4
• /
• pp.100-105
• /
• 2010

This study is to analyze the performance for ADS-B(Automatic Dependent Surveillance-Broadcast) operations by the Balanced Scorecard(BSC). It is also to collect the opinions of users(pilots, air traffic controllers and ground operators) relating ADS-B and to use the results as data about preparing political measures of aviation safety. For these purpose, BSC model redesigned on 4 different points of view is used for measuring the performance of the ADS-B operation. The proposed perspectives are affairs effectiveness, user orientation, system orientation and the capacity. As the results of this study, it is showed that the continuous development of ADS-B should be required and the users must be involved in the activities, additionally, the relevant authorities should try to be drawn the user-oriented results through the process.

• Knowledge Management Research
• /
• v.16 no.3
• /
• pp.81-102
• /
• 2015

With the rapid development of digital media, there has been a huge change in a way of communication, a process of information diffusion and a role of traditional media. Not like mass media, social media enables users to generate and tap into the opinions of a larger world. From that reason, social media is impacting marketing strategies. However, still social media marketing researches just focus on case study, analysis of users motivation or analysis of power user's usage pattern. Word-of-mouth has always been important especially in marketing area. In social media, word-of-mouth depends on each user that's why this research focuses on individual user's activity in SNS. I defined 4 factors (produce, diffusion, network size, activity of network size enlarge) that are effect on activity and verified hypothesis by multiple regression analysis, hierarchical regression analysis and moderated multiple regression.

• Journal of information and communication convergence engineering
• /
• v.10 no.1
• /
• pp.27-32
• /
• 2012

Twitter can spread and share all kinds of information such as facts, opinions, and ideas in real time. In this paper, we empirically compare and analyze the topic categories in Twitter with all top 100 users in each of geographic region. We mainly consider the relationships among regions and selected four regions: Global, Seoul, Tokyo, and Beijing. Each of the top 100 users in Twitter is classified into a specific category and then statistical analysis is conducted. Among eight topic categories, the "Arts" category is the largest and the second is "Life". The correlation between global and Seoul groups has the lowest value among the six pairs of relationships between regional groups, and this difference is statistically significant. We find that the Seoul, Tokyo, and Beijing regional Twitter groups, all in East Asia, have high topical similarity. Based on the correlation analysis, Seoul and Tokyo saliently show a sticky trend. The correlation coefficient presents very a strong positive correlation between Seoul and Tokyo. The correlation between the global group and the East Asian groups is relatively lower than that among the East Asian groups.

• Journal of the Korean Institute of Educational Facilities
• /
• v.17 no.2
• /
• pp.23-30
• /
• 2010

At present, the necessity of new design guidelines, evaluation and operation system for school facilities are on the rise according to re-edition of school curriculum in Korea. Moreover, it is necessary to procedure of the design, an institutional device and an ex post facto evaluation system for school facilities as a public building with the space planning that is suitable for various situations, which are able to collect users' various demands and opinions. Under the present situation, England has introduced and operated DQI system for the users' participation design of its. The present study will derive the meaning DQI system of England and how to operate it, and percuss the possibility of the application of design procedure of the education facilities in Korea.

• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 2005.05a
• /
• pp.232-239
• /
• 2005

Collaborative-filtering-enabled Web sites that recommend books, CDs, movies, and so on, have become very popular on the Internet. Such sites recommend items to a user on the basis of the opinions of other users with similar tastes. This paper discuss an approach to collaborative filtering based on the Simple Bayesian and apply this model to two variants of the collaborative filtering. One is user-based collaborative filtering, which makes predictions based on the users' similarities. The other is item-based collaborative filtering which makes predictions based on the items' similarities. To evaluate the proposed algorithms, this paper used a database of movie recommendations. Empirical results show that the proposed Bayesian approaches outperform typical correlation-based collaborative filtering algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.3
• /
• pp.1626-1638
• /
• 2019

Social Networking Sites (SNS) provide people with unique online social interaction environments where users can disclose their thoughts, feelings, and opinions to their personal contacts. Although previous studies have suggested that such activities produce positive effects on SNS user well-being, this study considered potential negative effects by investigating the relationship between SNS use and depression. In particular, This stydy examined how specific activities are related to different types of social comparison (upward/downward/horizontal) and how these different types of social comparison influence depressed moods among college students. The analysis of a survey of 245 Instagram users found that (1) looking at other people's status updates and commenting on other people's photos influences upward social comparison, (2) frequency of Instagram use predicts upward/downward/horizontal social comparison, and (3) upward social comparison was postively associated with depression, while downward social comparison was negatively associated with depression. Furthermore, the path anlaysis show that social comparison mediates the effect of Instagram use on depression. It suggests that Instagram use does not directly increase depression but it can lead to depression when social comparison on Instagram triggers depression.

• Journal of Information Processing Systems
• /
• v.17 no.3
• /
• pp.586-598
• /
• 2021

Nowadays, users' reviews and feedback on e-commerce sites stored in text create a huge source of information for analyzing customers' experience with goods and services provided by a business. In other words, collecting and analyzing this information is necessary to better understand customer needs. In this study, we first collected a corpus with 99,322 customers' comments and opinions in English. From this corpus we chose the best number of topics (K) using Perplexity and Coherence Score measurements as the input parameters for the model. Finally, we conducted an experiment using the latent Dirichlet allocation (LDA) topic model with K coefficients to explore the topic. The model results found hidden topics and keyword sets with high probability that are interesting to users. The application of empirical results from the model will support decision-making to help businesses improve products and services as well as business management and development in the field of hotel services.

• Journal of Internet Computing and Services
• /
• v.21 no.3
• /
• pp.29-39
• /
• 2020

Online communities, such as Internet portal sites and social media, have become popular since they allow users to share opinions and to obtain information anytime, anywhere. Accordingly, an increasing number of opinions are manipulated to the advantage of particular groups or individuals, and these opinions include falsified product reviews and political propaganda. Existing detection systems are built upon the characteristics of manipulated opinions for one particular time period. However, manipulation tactics change over time to evade detection systems and to more efficiently spread information, so detection systems should also evolve according to the changes. We therefore propose a system that helps observe and trace changes in manipulation tactics. This system classifies opinions into clusters that represent different tactics, and changes in these clusters reveal evolving tactics. We evaluated the system with over a million opinions collected during three election campaigns and found various changes in (i) the times when manipulations frequently occur, (ii) the methods to manipulate recommendation counts, and (iii) the use of multiple user IDs. We suggest that the operators of online communities perform regular audits with the proposed system to identify evolutions and to adjust detection systems.

• Proceedings of the KSR Conference
• /
• 2011.05a
• /
• pp.849-859
• /
• 2011

Before 2010, assignments proposed by government caused inconvenience of users(operation institutions & customers) as performing that National research organization suggested requirements from private organizations to special institutes, but now the institution of assignments is improving to reflect opinions from the present users. This is a study on methods for drawing a task of Rolling stock's core parts & enhancing of Urban Railway/Light Railway Transit. The definition of multiple stakeholders(local government, operation institution, research organization, academic world, the industrial world, etc.) related to rolling stock of urban railway/Light railway transit, experts in rolling stock and the application for designing of question items verified and designed through Delphi technique for objectivity, justness and fairness. Also, it is to draw a conclusion of assignments through a study on methods for drawing a task of Rolling stock's core parts & enhancing of Urban Railway/Light Railway Transit as sharing a process of assignments and integrating opinions of each stakeholder of urban railway/light railway transit.

• The Journal of the Korea Contents Association
• /
• v.9 no.7
• /
• pp.45-56
• /
• 2009

There are many internet users who collect the public opinions and express their opinions for internet news or blog articles through the replying comment on online community. But, it is hard to search and explore useful messages on web blogs since most of web blog systems show articles and their comments to the form of sequential list. Also, spam and malicious comments have become social problems as the internet users increase. In this paper, we propose a clustering and visualizing system for responding comments on large-scale weblogs, namely 'Daum AGORA,' using similarity analysis. Our system shows the comment clustering result as a simple screen view. Our system also detects spam comments using Needleman-Wunsch algorithm that is a well-known algorithm in bioinformatics.