• Korean Journal of Culture and Social Issue
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• v.16 no.3
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• pp.289-310
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• 2010

The purpose of this study was to examine how political interest, political ideologies, and information-searching goals influence the amount of information voters search, the ways in which people search for information about political candidates, and the type of information they select. The results showed that the participants under accuracy goal searched much more information and the participants under the high level of interest were not affected by conservative ideology, but the participants with the low level of interest were influenced by the liberal ideology and viewed substantially more information. And most of participants had the attribute-centered searching pattern. The social policies were accessed most, however, the information about party and personal background of a candidate were found least.

• Korean Journal of Artificial Intelligence
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• v.12 no.2
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• pp.9-16
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• 2024

In this study, we delve into the effects of personalization algorithms on the creation of "filter bubbles," which can isolate individuals intellectually by reinforcing their pre-existing biases, particularly through personalized Google searches. By setting up accounts with distinct ideological learnings-progressive and conservative-and employing deep neural networks to simulate user interactions, we quantitatively confirmed the existence of filter bubbles. Our investigation extends to the deployment of an LSTM model designed to assess political orientation in text, enabling us to bias accounts deliberately and monitor their increasing ideological inclinations. We observed politically biased search results appearing over time in searches through biased accounts. Additionally, the political bias of the accounts continued to increase. These results provide numerical evidence for the existence of filter bubbles and demonstrate that these bubbles exert a greater influence on search results over time. Moreover, we explored potential solutions to mitigate the influence of filter bubbles, proposing methods to promote a more diverse and inclusive information ecosystem. Our findings underscore the significance of filter bubbles in shaping users' access to information and highlight the urgency of addressing this issue to prevent further political polarization and media habit entrenchment. Through this research, we contribute to a broader understanding of the challenges posed by personalized digital environments and offer insights into strategies that can help alleviate the risks of intellectual isolation caused by filter bubbles.

• The Journal of Information Systems
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• v.26 no.3
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• pp.171-185
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• 2017

Purpose Recently, there has been an increase in attempts to analyze social phenomena, consumption trends, and consumption behavior through a vast amount of customer data such as web search traffic information and social buzz information in various fields such as flu prediction and real estate price prediction. Internet portal service providers such as google and naver are disclosing web search traffic information of online users as services such as google trends and naver trends. Academic and industry are paying attention to research on information search behavior and utilization of online users based on the web search traffic information. Although there are many studies predicting social phenomena, consumption trends, political polls, etc. based on web search traffic information, it is hard to find the research to explain and predict tourism demand and establish tourism policy using it. In this study, we try to use web search traffic information to explain the tourism demand for major cities in Gangwon-do, the representative tourist area in Korea, and to develop a nowcasting model for the demand. Design/methodology/approach In the first step, the literature review on travel demand and web search traffic was conducted in parallel in two directions. In the second stage, we conducted a qualitative research to confirm the information retrieval behavior of the traveler. In the next step, we extracted the representative tourist cities of Gangwon-do and confirmed which keywords were used for the search. In the fourth step, we collected tourist demand data to be used as a dependent variable and collected web search traffic information of each keyword to be used as an independent variable. In the fifth step, we set up a time series benchmark model, and added the web search traffic information to this model to confirm whether the prediction model improved. In the last stage, we analyze the prediction models that are finally selected as optimal and confirm whether the influence of the keywords on the prediction of travel demand. Findings This study has developed a tourism demand forecasting model of Gangwon-do, a representative tourist destination in Korea, by expanding and applying web search traffic information to tourism demand forecasting. We compared the existing time series model with the benchmarking model and confirmed the superiority of the proposed model. In addition, this study also confirms that web search traffic information has a positive correlation with travel demand and precedes it by one or two months, thereby asserting its suitability as a prediction model. Furthermore, by deriving search keywords that have a significant effect on tourism demand forecast for each city, representative characteristics of each region can be selected.

• International Commerce and Information Review
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• v.7 no.4
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• pp.271-285
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• 2005

Korean Government has been actively and aggressively promoted the global e-commerce (or e-trade). However, the global researches regard the Korea as the passive or retrogressive country in e-trade. The purpose of this study is to clarify the change of the policy paradigm on the e-trade of Korea and to search for new paradigm based on the total amendment (or inauguration) of the e-trade promotion law. The research concludes the current political paradigm on "the Designated total solution provider" should be separated from the e-trade infra or platform. More competitive and market-oriented paradigm of the promotion support on e-trade metamediary should be evaluated in terms of facilitator, service provider and collaborator.

• Journal of Information Management
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• v.38 no.3
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• pp.1-30
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• 2007

The purpose of this study is to analyze the political and functional requirements of the regional library portal and to evaluate such requirements. A literature review was carried out to discuss library portal, and introduce the best practices of the regional library portal. After analyzing the political and functional requirements of the regional library portal, AHP was applied to evaluate requirements. In the political requirements, standards, digital collection development, operation and evaluation were ranked according to importance, and copyright & licence management which belongs to digital collection development was underrated. There were differences in the importance among the functional requirements of the regional library portal, integrated search, integrated interface, information service, separated digital collection management and access management were ranked according to importance.

• IE interfaces
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• v.9 no.1
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• pp.83-93
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• 1996

In a very time, the Internet has affected the lives of millions of peoples. Some serious advances have been made in software development, information exchange, publishing, database retrieval, educational opportunities, commercial expansion, political awareness, and more. But this network of network is still in its infancy. More advanced search concept, World Wide Web(or Web) will continue to help users move boldly onto the information highway. It help user work effectively and efficiently. In this article, we explain how to utilize web to enhance research in Industrial Engineering area.

• Journal of Korea Multimedia Society
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• v.21 no.3
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• pp.369-381
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• 2018

Nowadays a personalization algorithm is gaining huge attention. It gives users selective information which is helpful and interesting in a deluge of information based on their past behavior on the internet. However there is also a fatal side effect that the user can only get restricted information on restricted topics selected by the algorithm. Basically, the personalization algorithm makes users have a narrower perspective and even stronger bias because users have less chances to get views of opponent. Eli Pariser called this problem the 'filter bubble' in his book. It is important to understand exactly what a filter bubble is to solve the problem. Therefore, this paper shows how much Google's personalized search algorithm influences search result through an experiment with deep neural networks acting like users. At the beginning of the experiment, two Google accounts are newly created, not to be influenced by the Google's personalized search algorithm. Then the two pure accounts get politically biased by two methods. We periodically calculate the numerical score depending on the character of links and it shows how biased the account is. In conclusion, this paper shows the formation process of filter bubble by a personalization algorithm through the experiment.

• Korean Management Science Review
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• v.16 no.2
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• pp.93-108
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• 1999

There seems to be a renewed interest in interorganizational relationship to search ofr strategic information partnerships. It is particularly noteworthy that no study has yet reported configurations at the level of interorganizational relationships nor compared such configurations across different types of IOS(interorganizational Infromation System). This paper seeks to uncover dominant configurations of interorganizational relationships across the various types of IOS. We integrate relevant theoretical concepts from transaction cost economics, organization theory and political economy to develop a conceptual model of interorganizational relationships based on the fit between information processing needs and information processing capabilities. We empirically uncover a set of hypothesis toward the patterns of interorganizational relationships. Moreover the implications for further research pertaining to the logic and development of configurations were proposed.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.93-111
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• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.

• Iberoamérica
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• v.12 no.2
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• pp.383-428
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• 2010

To make a critical revision on the inherited social problems throughout the time in Mexico, not always turns out to be easy task, especially when the subject is lent to approach it from diverse perspective, one of them, the educative one. To analyze the low quality of the educative supply is complex subject. One of the maximum profits of institutional revolutionary Mexico was the creation of the Public Education Ministry in 1921. In the post-revolutionary and modern period, the seventies were characterized to be applied to the growth the infrastructure and the fortification of the educative system following the policy of "modernization and development". From the eighties, to lift the quality of the education was considered like one of the specific rules in the strategy of the call "educative revolution". In the nineties, through political programs and agreements, structural changes within the educative system were carried out with the intention to lift the quality of the services. In synthesis, the perspective in the educative policy of Mexico during the last thirty years of century xx, or post-revolutionary period, can be understood, from at least five specific conditions: educative profits in cover, modifications in the educational programs and contents, profits in the political agreements between the agents who take part within the educative system, changes and modifications to the laws applicable to the education, and; the search of the fairness through the compensatory programs. This paper tries to give answer to questions such as: The educative system reflects the ideals of the revolution? The present educative system is the product of a truncated revolution or the fruit of an untimely democracy?