• 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.

• Journal of Distribution Science
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• v.18 no.6
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• pp.5-14
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• 2020

Purpose: This study was based on curation commerce that has been rapidly developing. It looked into the effect of curation commerce's quality of service factors (information quality, information interest quality, interaction quality, and personalization quality) on satisfaction and the mediating effect of consumer empathy and shopping value between service qualities and consumers' satisfaction with curation commerce. Research design, data, and methodology: The survey was conducted on 273 consumers who used Chinese curation commerce services. The research data was analyzed using the Smart PLS 3.0 program. The empirical analysis was conducted with reliability and validity analyses of the questionnaire and hypothesis test. Results: As a result, only the quality of information had a direct impact on satisfaction. The remaining service quaility factors (information interest quality, interaction quality, and personalization quality) were found to affect satisfaction through utilitarian value or consumer empathy. Conclusions: This study is meaningful in that it selected the service quality factors experienced by consumers about curation commerce services in line with the bright market prospects of curation services. In addition, the significance of this study was to reveal the psychological mechanism of the process in which the quality of service reaches consumer satisfaction.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2008.10a
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• pp.106-112
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• 2008

Personalization is user oriented dynamic method based on user preferences for easy access to what users want to view or get. It has become more important in mobile domain with rapid growth of wireless Internet and mobile phone market after success of web based market and therefore, it can be applied to service of spatial analysis result. In this paper, spatial analysis using user profile and notification service methods are proposed as one of personalized spatial data service methods for mobile users. A service system for spatial analysis with user profile is designed to prove possibility of spatial analysis based on user preferences and notification service is also designedto show generated output can be sent to user's mobile devices efficiently to make users informed of preferred information. Prototype system is implemented and it is applied to real estate data that has many selectable conditions by users. Information service based on user preferences can be applied to spatial data by using proposed system and it is efficient when cache module is used to shorten response time. Various user models for application domains and performance evaluation methods need to be developed in the future.

• Journal of the Korea Society of Computer and Information
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• v.18 no.9
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• pp.153-163
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• 2013

As the number of Smartphone users increases, mobile advertising market has been expanding rapidly. In line with this, the ways to evaluate mobile advertising effectiveness are diversified, and engagement is one of the crucial qualitative and multi-dimensional evaluation methods of mobile advertising. Thus, the purpose of this study is to identify key antecedents and consequences of mobile advertising engagement, and examines the structural relationships among those research variables. Informativeness and personalization were selected as antecedents of engagement, trust and e-WOM intention were selected as consequences of engagement based on the review of previous studies. Data collected from survey was used to assess research hypotheses. Results show that informativeness and personalization have significant and positive effects on engagement, and engagement influences on trust and e-WOM intention. In addition, trust is proven to be positively related to e-WOM intention.

• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.219-226
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• 2005

This paper describes the open API with integration of semantic web service with PARLAY X based open API in 4G mobile network. It can be expected that the intelligence such as the context-awareness, adaptation and personalization in 4G mobile network will be deployed. But the existing PARLAY based network lacks in considering context-awareness, adaptation and personalization. Therefore, the object of this paper is to support the architecture and the Application Programming Interface (API) of the network service for the context-awareness, adaptation and Personalization in 4G mobile network The open API is to provide users with the adaptive network service to the changing context constraints as well as detecting the changing context and user's Preference. For instance, the open API can Provide users with QoS in network according to the detected context and user's preference, after detecting the context such as location and speed and user's preference.

• Journal of the Korean Society for information Management
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• v.25 no.4
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• pp.205-226
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• 2008

The success of social networking sites (SNSs) may depend on many factors. Continuance use of SNSs is one of these. Especially, in the Web environment where users can leave one service with a single mouse click, maintaining existing members cost much time and efforts. Without continuance use of SNSs, SNS-based service would not create any value. This study focused on identifying factors influencing users' continuance intention in SNSs. Based on relevant literature review, six influencing factors were initially identified. They were reputation, relational capital, knowledge quality, compatibility, personalization, and satisfaction. Web-based questionnaire survey was conducted and a total of 325 usable responses were collected. Reliability test and two rounds of exploratory factor analyses resulted in identifying five factors. The relationship between the factors and the continuance intention was tested by using multiple regression analyses. The analyses revealed that satisfaction was the most significant factor. Knowledge quality and relational capital also had significant effects while reputation and personalization did not have significant effect on continuance intention. Instead, reputation and personalization showed significance in influencing satisfaction.

• The Journal of Society for e-Business Studies
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• v.13 no.2
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• pp.117-147
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• 2008

Developing various ubiquitous computing services (U-services) is being propelled throughout the industry. As U-services are being penetrated into our daily life, research on the factors influencing the acceptance of U-services is highly needed. In this line of study, we examined previous literatures about information technology acceptance and UTAUT model, and applied UTAUT model to U-service acceptance. To characterize the U-services into our research model, we newly introduced 'context based personalization' factor. Since the respondents could not directly experience the U-services yet, we adopted scenario-based questionnaire. For this, we deliberately developed U-service scenario. And then this U-service scenario is verified using capability-based assessment method. Using data collected from 251 respondents, this study found that 'context based personalization' factor was positively and significantly related to the acceptance of U-service as well as UTAUT model's 4 factors such as performance expectancy, effort expectancy, social influence and facilitating conditions.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.11
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• pp.475-482
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• 2013

Several approaches to recommendation systems have been studied. One of the most successful technologies for building personalization and recommendation systems is collaborative filtering, which is a technique that provides a process of filtering customer information based on such information profiles. Collaborative filtering systems, however, have a sparsity if there is not enough data to recommend. In this paper, we suggest a movie recommendation system, based on the weighted personal propensity and the collaborating filtering system, in order to provide a solution to such sparsity. Furthermore, we assess the system's applicability by using the open database MovieLens, and present a weighted personal propensity framework for improvement in the performance of recommender systems. We successfully come up with a movie recommendation system through the optimal personalization factors.

• Journal of Fashion Business
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• v.22 no.6
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• pp.70-82
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• 2018

In modern society, the means of sharing information has expanded from existing personal computers and mobile devices to a variety of smart devices rapidly increasing information production. Recently, curations have extended to online businesses. There has been wide use of curation services in the cosmetics curation market. In this study, focuses on factors which cosmetics curators have in mind. In relation to the impact of cosmetics curation quality properties on usability, the effects of the medium of satisfaction and confidence are to be verified. For this study, a survey of 378 women in their 20s and 40s who had experience with curations was done and the collected data were analyzed using SPSS 23.0 and AMOS 23.0 statistics programs. The results showed that information quality and personalization quality of cosmetics curation service were important factors affecting customer satisfaction. Personalization quality also had a positive effect on trust. System quality has a positive impact on trust and further influence on intention to use. This indicates that the trust on the curation service depends on the stability of system. However, design quality was found to have no significant effect on satisfaction and trust. In future, the research related to application and utilization of big data-based cosmetic curation will be further expanded.

• Journal of Korean Library and Information Science Society
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• v.53 no.3
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• pp.287-314
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• 2022

The purpose of this study was to present a content curation strategy of the university library to support user learning and research. As a method to achieve the purpose of the study, first, the concept of content curation was examined through literature research. After that, implications were found by analyzing the cases of content curation services such as university libraries, national libraries, and content companies. As a result of the study, five strategies for successful content curation of university libraries were proposed: providing high quality contents, performing preemptive information service roles, keep content up to date, securing interactivity through user participation, and developing personalization algorithms.